Design Thesis "Building Like Animals- using autonomous robotics to search, evaluate and build"

UNIVERSITY OF MELBOURNE

BUILDING LIKE ANIMALSARCHITECTURE DESIGN THESIS

USING AUTONOMOUS ROBOTS TO SEARCH EVALUATE AND BUILD

JUAN YANG

BUILDING LIKE ANIMAL | 2014 ARCHITECTURE DESIGN THESIS JUAN YANG

PROGRAMME

COURSE DURATION

NAME

DEPARTMENT

UNIVERSITY

TITLE

TUTOR

SUBMISSION TIME

Architecture Design Thesis

Sem 2, 2014

Juan Yang (355396)

Master of Architecture

University of Melbourne

Building Like Animals

Stanislav Roudavski

05/11/2014

/ 003

[email protected]

ACKNOWLEDGMENTS

A special note of thanks to Dr. Stanislav Rou-

davski, Senior Lecture in Architectural Design

and my thesis tutor in the University of Mel-

bourne.

I would like to thank the mechanical engineering

students for making the robots, it is a nice expe-

rience working with you.

/ 005

INTRODUCTION | 008

0.1 STUDIO INTRODUCTION

0.2 BACKGROUND

PROJECT | 022

1.1 THESIS AND STATEMENT

1.2 UNPREDICTABLE ENVIRONMENT

1.3 BUILD BY WASTE

1.4 LEARNING FROM ANIMAL

1.5 SIX-AXIS ROBOTICS

1.6 SPECULATIVE PROTOTYPES

1.7 CRITICAL FUTURE USE SCENARIOS

RESEARCH

2.1 SPECULATIVE DESIGN

2.2 ANIMAL ARCHITECTURE

2.3 COMPUTATION PROGRAMMING

2.4 ARTIFICIAL INTELLIGENCE

2.5 ROBOTICS IN ARCHITECTURE

CODE LEARNING OUTCOME

REFERENCE

APPENDICES

5.1 MID-TERM MOVIE SCRIPT

5.2 FINAL MOVIE SCRIPT

/ 007

INTRODUCTION & BACKGROUND

Background introduction to topics of Complex and system thinking in

architecture, computation creativity, animal architecture, robotics in

architecture, and autonomous architecture.

0 / 009INTRODUCTION

This thesis This studio “Autonomous Architecture

Studio” is my thesis studio for Master of Architecture

in the University of Melbourne 2014, led by Stanislav

Roudavski and Denny Oetomo. With cooperation

and collaboration of architectural and mechanical

engineering (from Robotics Automation group)

students, is aimed to explore robotics potential in

autonomous architectural design.

The learning outcomes of this studio are 1) Speculative

design includes system thinking, hybrid ecologies and

animal architecture. 2) Creative technical practice

includes algorithmic thinking and programming &

mechatronics and robotics. The main softwares are

being used in this studio are processing and arduino.

Kinect will also be applied to scan the environment.

The book mainly contains two parts, the first part is my

speculative design progress from visual algorithm to

physical prototypes, and the second part is background

research in theories, technologies and case studies.

0.1 STUDIO INTRODUCTION

/ 011INTRODUCTION

The employment of study in other fields such as tech-

nology and biology is opening up potentials for archi-

tects to rethinking architecture in many perspectives

from architectural design to building culture.

This part gives some background introduction on

complex system thinking in architecture; computational

creativity; animal architecture; robotics in architecture;

and autonomous architecture.

0.2 BACKGROUND

/ 013INTRODUCTION

Algue, Ronan and Ewan

Bouroullec, 2004. Using

small plastic, organic-look-

ing elements that can be

linked together to f ilter

the light and insulate or

permeability space through

the assembly of a module.

COMPLEXITY AND SYSTEMS THINKING IN ARCHI-

TECTURE / "Speculative Design aims to open up new

perspectives on "wicked problems", to create space for

discussion and debate about alternative ways of being,

and to inspire and encourage people's imaginations."

(Anthony Dunne & Finoa Raby, 2013)

System thinking descripes the interconnection

and interactions Swarm intelligence, multi-agents

behaviors, interactive design etc has been more

frequently introduced to architecture spculative

thinking.

----------------------------------------------------------

Speculat ive Everything - Design, Fict ion, and

Social Dreaming, 2013, Massachusetts Institute of

Technology.

ARCHITECTURE

EMERGENT BEHAVIOR

FUNCTIONBEHAVIOR

COMPLEXITY“ILITIES”

/ 015INTRODUCTION

COMPUTATIONAL CREATIVITY / The role of computation within

highly speculative approaches to architectural design. The natural

of complex systems and their indeterminacy in opposition to the

role of computational design in exercising hierarchical control.

The emergence of complexity theory reminds people to rethink

our understanding of formation and the volatility of their process-

es. The conceptualizations of form has shifted from the macro

scale to a concern for the operation of the complex systems that

underlie formation. The inspiration of swarm intelligence, emer-

gent behaviors of multi-agent systems can be simulated and

thought through computation. Those behaviors shift from top-

down “form matters” towards bottom up “form

emerging from the interaction of localized entities

within a complex system”.

The world is dynamic, processuality is all around

us - the growth of plants, the air, the live and

death. Softwares like SketchUp can only visualize

a static model. However, algorithms and scripts

can run as a process with input and output vari-

ables relating to datasets. Algorithms manifest

dynamic and emergent behaviors.

----------------------------------------------------

Luciana Par is i , Contag ious Archi tecture:

Computation, Aesthetics and Space, Cambridge:

MIT Press, 2013.

“ a consideration of algorithmic architecture can assist us in understanding

algorithms as actual objects: as spatiptemporal data structures that are inter-

nally conditioned by infinites as incomputable entities.” -Luciana Parisi

Soft Structures, Expanded

Environment, 2014. Soft

structure projects assume a

local separation of species.

“Synanthropic Habitats” in

bio-inclusive architecture

grouped into Synanthropic

Habitats, Soft Structures

and Post-Animal Projects.

/ 017INTRODUCTION

ANIMAL ARCHITECTURE / Human architecture has been inspired from animal

architecture for over centuries. The study shifts from learning the forms of ani-

mal architecture to the process and behaviors in building.

The nests of social insects are the result of the collective building activity of ma-

ny individuals. New structures are added on the old ones to meet the require-

ment of growing colony. The integration of nest structure is very naturally relies

on the feedback between forms, dynamical properties and growth of new forms,

the process and growth are dynamically. The phenomenon of stigmergy in social

insects enable the individuals be mobile and be able to modify their environment

and affect future behavior.

Many animals especially social insects are single-minded and self-organized

Each worker’s action is governed by sets of relatively simple behavioral rules

and controlled by individuals. Efficient transportation of materials and informa-

tion is essential to maintaining the nest structure and organization.

Up: Termites mould sitting

on the ground. It goes into

deep and has ventilation

system.

Right: Weaver Bird woven

nests. This male bird’s nest

is woven from leaf-fibers,

grass and twigs.

/ 019INTRODUCTION

Ant Robots. U.S. scientists

from Harvard University and

Wyss Institute for Biolog-

ically Inspired Engineering

builds these self-organizing

robots.

ROBOTICS IN ARCHITECTURE / Robotics will have big

impacts on architcture and construction industry over the

next few years. They have benefits on minimizing manual

labor and cost, and thus improving efficiencies. With the

development of digial architecture for these years, the

involvement of robotics in architecture is opening up new

aesthetic and functional potentials that coulld change

architecuture desing and building culture.

Like computers, industrial robots are suitabe for a wide

virety of tasks because they are 'generic' and therefore not

tailored to any particular application. The range of robotic

process is gradually expanding from prefabrication towards

direct use of robots on the construction iste and involving

in design process. The involvement of robotics shifts design

process from predetermind idea towards to follow the

logic of the given materials. Robots are now connecting

technology and knowhow, as well as imagination and

materialization. Architecture begins to develop an adequate

material practice for the cultural logic of the information

age.

AUTONOMOUS ARCHITECTURE / The

technology innovation in architecture extends

the boundary. Currently the autonomous re-

action to environment in architecture applies

mainly in facade system. Interactive architec-

ture, kinetic architecture, robotic architecture

have potential to achieve greater automation

in architecture system

Stone Spray, is programmed

to function like a 3D printer,

Combining sand, soil, and a

special binding ingredient

to create fully formed archi-

tectural object of designers’

choosing.

/ 021INTRODUCTION

PROJECT

The project part includes speculative thinking and prototype in ro-

botics in architecture and inspired by animal architecture; potential

areas of application in architecture and future research. The research

topic is using autonomous robots in searching, sorting and building in

dynamic environment. “Beyond semantics, two concrete trends are happening. On

one hand, human-made things are behaving more lifelike; on

the other hand, life is becoming more engineered.“- Kevin Kelly

1“Beyond semantics, two concrete trends are happening. On

one hand, human-made things are behaving more lifelike; on

the other hand, life is becoming more engineered.“- Kevin Kelly

/ 023

Typical architecture design is

prescriptive and reliant on top-

down decisions. It also relies on

specially prepared construction

sites and is limited in its capacity

to design in undisturbed natural

l oca t ions . Moreover, t yp ica l

outcomes of current architectural

processes are static configurations

of standardized industrial parts. By

contrast, this thesis rethinks the

relationship between architecture

and env i ronment in dynamic

and unpred ic tab le . In do ing

so, it utilities an understanding

of env i ronments as dynamic

1.1 THESIS

ecosystems. In animal architecture,

such as bird nests and termites

moulds, the building site’s location

and character, and material are

not entirely predictable and thus

require adaptation. Attempting

to make architectural design

more f lex ib le, decentra l ized,

and natural inspired. Staging a

practical experiment in response

to these goals, this thesis focuses

on the capabilities in searching,

evaluating and assembling building

materials by autonomous robots in

a dynamic environment.

STATEMENT / The project is constructed in three

parts; the first part explores the theoretical framework

and precedents in speculat ive design, animal

architecture, artificial intelligence and robotics in

architecture. In the second part, I virtually visualize the

design process algorithm in Processing, and build a

physical prototype by two robotic arms for simulating

the concept of this thesis. The final stage is the

potential future speculation based on this project.

The design goad for this thesis is to define a site

location by analyzing the environment, searching for

materials (using A* algorithm), evaluating materials

costs such as quality and proximity (using the Kinect

sensor), and bringing the selected potential building

components to the site of construction and assembling

them by two collaborative robotic arms.

This research helps to visualize possible approaches

to architectural design and construction in the future

because it has potential to dealing with unpredictable

or hazardous environment. Currently, the behavior-

based robots are used in hazardous situations such

as aerospace research, the nuclear industry, and the

mining industry. This thesis seeks to demonstrate that

they also have great potential to extend the capabilities

of architectural design in dealing with complex,

dynamic and complexly interconnected environment.

Moreover, these mobile robots have benefits in cost

saving, easy assembling and operating.

/ 025RROJECT

PREPARED CONSTRUCTION

SITE

STATICCONFIGURATION

HIERARCHICAL

CONTROL

DYNAMIC / UN-PREDICTABLE ENVIRONMENT

NOT ENTIRELY PREDICTABLE

ARRANGEMENT

LEARNING FROM ANIMAL

SIMPLIFIED CONTOUR

(DEPTH IMAGE)

3 TYPES OF MATE-RIALS

(BY LENGTH)

6-AXIS ROBOTIC ARMS

EARTHQUAKESITE

SEARCHING USE-FUL MATERIALS

ON SITE

BEHAVIOR -BASED

ROBOTICS

TYPICAL ARCHITECTURE SPECULATIVE THINKING PROTOTYPE TESTINGPOTENTIAL APPLICATIONV.S.

/ 027RROJECT

Typical architecture relies on prepared construction istes and is

limited in its capacity to design in undistrubed natural locations

or sites having potential safety concerns such as after natural

diaster. The technology improvement and robotics development

have potential to extend architecture in these field in future.

In this thesis project, I chose earthquake sites as my design

concern, where the roads are destroyed, cars and trucks are

difficult and dangrous to get in, and aftershock increase the

dangrousness. The small behaviour-based robots could access

to the site and searching for suitable material elements and build

temporary housing.

1.2 UNPREDICTABLE ENVIRONMENT

Right One: Sichuan earth-

quake site

Right Two: Roads are cut

after the earthquake

Right Three: Housing on the

mountains after earthquake

Right Four: Undistributed

bay

Right F i v e : Abandoned

industrial site

Right Six: Undistributed

natural forest

/ 029RROJECT

Top left: Indian and Paki-

stani Kashmir earthquake

2005

Top right: Sichuan province

China earthquake 2008

Bottom left: Haitai earth-

quake 2010

Bottom right: Japan earth-

quake 2011

EARTHQUAKE

The 20th century was marred by numerous deadly

earthquakes that claimed lives of many thousands of

people and flattened several towns around the world.

2013 Solomon Islands: Three villages were flattened

when a trunami triggeed by an 8.0-magnitude quake

crashed ashore.

2011 Japan: More than 19,000 were killed when a

tsunami triggered by an undersea quake slammed into

the northeast cost, triggering a nuclear crisis at the

Fukushima Daiichi atomic plant. Magnitude 9.0

2011 Haiti: Between 250,000 and 300,000 killed

when a quake hits what is already one of the world's

poorest countries, devastating the capitl Port-au-

Prince. Magnitude 7.0

2008 Sichuan Province China: 87,000 dead or

missing. A large number of children are among the

dead, with shoddily-built schools bamed. Magnitude

8.0

----------------------------------------------------------

Chronos and Factsheets, Deadliest earthquakes and

tsunamis of the past century, 2013, Tengrinews

Earthquakes Mapping since

1890 by magnitudes. NASA’s

Visual Earth

/ 031RROJECT

/ 033

Left:Haiti shelters rein-

forced by multiple tarps

Middle Top: Haiti shelter.

Haiti has only 2.5 % forest

cover, making wood mate-

rials scarce. The wood to

build this tent was bought

not scavenged.

Middle Bottom:The moun-

tains in some region have

meant temporary housing

cannot be bui l t easi ly.

Rescuers have been re-

questing temporary housing

elsewhere.

Right Top: A family in Cite

Soleil f inds shelter in a

makeshift tent city after

Haiti’s violent earthquake

le f t many bu i ld ings in

ruins.2010 Photo by Logan

Abassi

Right Bottom: Yunan earth-

quake, people are waiting

for rescue.

UNRESCUED LIVING CONDITION

I take earthquke site as background context in this thesis. People

who suffered the diaster and have poor living conditions after the

eathquake. Especially in poor region like Haiti, which more than

70% of people in Haiti were living on less than $US2 per day.

In the 7.0 Magnitude Quake 3,500,000 people were affected

by the quake, and 220,000 people estimated to have died,

over 188,383 houses were badly damaged and 105,000 were

destroyed by the earthquake, 1.5m people became homeless.

After four years, many people are still living under very bad

conditions.

Sometimes the goods and materials are very difficult to transport

into because the roads are cut and aftershock may happen. I

purpose if we can send the small scale behavior based robots

into the earthquake site, and let them searching for suitable

materials and bringing to a calculated safty site, and assembling

these materials for tenporary shutter for people. in diaster region.

----------------------------------------------------------

Haiti Earthquake Facts and Figures, Disasters Emergency

Committee.

RROJECTRROJECTRROJECTRROJECT

/ 035RROJECTRROJECT

Left Top: Shelters after Haiti

Earthquake

Left Bottom: Sleep Box

made by cardboard earth-

quake evacuation shelter,

can provide privacy.

Left Bottom: Typical Haitian

temporary shelters issued

by current government

Middle: Tent-School in

Sichuan after earthquake

provided by Chinese govern-

ment

Right Top: A tent city in the

village of San Geogorio, six

miles from where the earth-

quake stuck. Photograph:

Andreas Solaro

Right Bottom: Shigeru Ban

designed emergency refugee

shelters for post-civil-war

Rwanda, and homeless after

Japan’s Kobe earthquake

and Haitian Earthquake.

RESCUED LIVING CONDITION

The temporary rescued accomodations have cultural

difference. In Japan, privacy is a serious issue for

refugees. People normally will live in school. gyms

and places have empty space, divided by temporary

partitions. After the Tohoku quake, many architects

have created prototypes for simple shelters that can

prodivde some relief in terms of privacy and integrity to

evacuees.

In many earthquake regions, people will live in tents

made by plastic cover (some are metal) and metal

skeleton that provided by government. In 2008 Sichuan

Earthquake, most of the survivors are taking shelter

under self-made temporary tents, although many are

living without any shelter at all. Rainfall is making

things worse-hindering the rescue work and worsening

the living conditions of the survivors.

----------------------------------------------------------

William, Sleep Box is Personal Cardboard Earthquake

Evacuation Shelter, Japan Trends, 2012

The affordable earthquake resistant, hurricaine

resistant, self-contained 'green' shipping container

home with solar power proposed for Haiti and other

areas hit by disaster or living in prverty proposed by

architect Darrin Badon. He envisioned small clusters of

20-25 shipping container homes forming a small clse

knit community.

The Folding Bamboo House, designed by Ming Tang,

is contructed from bamboo and recycled paper and

can be cheaped manufactured. Tang designed the

geometric folding structure after a 7.9 earthquake hit

central China. The structures can be folded into many

different shapes, allowing a range of structures to be

created.

This project proposed temporary playground equipment

for children living in the temporary housing in Tohoku

area as a consequence of 2011 Tohoku earthquake

and tsunami. It is made by thin plastic paper for

children to assmeble.

The first response emergence sheter is easy to

transport and set up requires only one person Made

out of polypropylene, the shelter can form many

shapes and provides relief for up to 4 peope, while

rainwater can be collected from the folds.

The monolithic domes designed by the California

Institute of Earth Art and Achitecture for disaster

resistence.The ceramic CalEarth shelters are made

from four natural elements (earth, water, air and fire)

using just three steps: dig up the grond, place earth

into sacks, and pile them up and dix them in place.

/ 037RROJECT

INNOVATIVE TEMPORARY SETTLEMENT

Mnay architects and designers are seeking

for innovation solutions for temporary shulter

dealing with natural diasters. They are eitiher

using local materials / resources or they are

light weighted, easily folded and transported.

A l l th ree images f rom

Sichuan earthquake site,

the potential materials to

be collected could be wood

sticks, steel frames, and

bricks.

/ 039RROJECT

POTENTIAL MATERIALS UES IN EARTHQUAKE SITE

I think it will be good if the robots can collect the sutibable

building elements if the emergency shulter (like tent) cannot

be transported into the diaster site. The suitbale elements

are cultural differentiated. It could be bricks, wood / steel

frames, metal sheet, bamboo etc.

Building by waste and recycled materials is a crucial

study in recent years. In this thesis project, on

earthquake site search and assemble is also a way

building by recycle materials. Hence, the study of

building by waste and understand the properties are

essential for this project.

1.3 BUILDING BY WASTE

ELEMENTDIMENSION

MATERIALPROPERTY

MATERIALCOLOR

SIMPLE COMBINATION

/ 041RROJECTRROJECT

Above: Book Cell, Built by 7,000 Recycled Phone Books. Matej

Kren. 2010.

Below: Built by recycled materials of bottles. Jasmine Zimmerman,

Above. The ball-shaped shelter, built from FSC-certified wood and

a variety of scrap materials. Gert Eussen. 2012

Below: Plastic Frantastic. Build out of 10000 plastic soda bottles

in Piedade slum, north of Rio d Janeiro.

Above: The Big Church, a recyced building made from a heap of

discard objects.

Right: Building with Pop Cans, sustainabily built and functioning

houses in Colorado. Michael Peynolds, 2011

Above: Sculpture "Sound Wave" out of melted vinyl records, Jean

Shin, 2007

Right: "To Live" a shelter created from real estate signs to make a

statement of homelessness and sustainbale building. Nick Sayer.

2009

Left: Temporary shelter built by soap cans. Bat Yam, Iseal. 2011

Below: Recycled Windshield Greenhouse, are busting out of the

woodwork. Sebastien Ramirez, 2010

BUILT BY RECYCLED MATERIALS

Building by waste materials have benefits in

sustainable development, cost efficiency. The

arrangement of modulation and repetition has po-

tential to create both in aesthetic and functionality,

as well as making a statement.

Since the architecture of recycling waste has

characteristics in one or few standardization in

dimensions / textures / color / materials / weight

and etc. So they could be searched, sorted and

collected by autonomous robots for recognizing

these characteristics.

Above: Sculpture "Sound Wave" out of melted vinyl records, Jean

Shin, 2007

Right: "To Live" a shelter created from real estate signs to make a

statement of homelessness and sustainbale building. Nick Sayer.

2009

Left: Earthship Building. Nestled into the ground and require a

solid rear wall construction to etain the earth.

Monica Holy.

Below: Cover 10-Storey Building with 1,000 Recycled Doors. South

Korean artist Choi Jeong-Hwa.

/ 043RROJECT

A PLOT is a thesis group

project at Taubman College.

The idea is focusing on

material culture and spatial

implications speculation

alone misses the unexpect-

ed push of reality.

Middle and Right: Skyscrap-

er by Projeto Coletivo in

Curitiba, Brizil. The future is

the use of garbage both as

an agent of social change

and as a physical element

of construction. The idea is

that the residents will work

on the bottom of the build-

ing as a factory, recycling,

cleaning and select ing

waste, previously taught by

experts in the field. This

material will be used on the

building’s construction and

also for crafts, urging cre-

ativity of the own workers.

/ 045RROJECT

In this thesis, process and behaviors of bird nestis and termites

moulds are the initial inspiration for the design speculation. I took

Baya Weaver as a case study for analysing from defining the

nest location, to searching suitable materials, and to assemble

the materials to the nest with certain logics. More research on

animal architecture please go to 2.2 Animal Architecutre in this

book.

1.4 LEARNING FROM ANIMALRepresen ta t i on o f the

process of Baltimore oriole

nest construction in Avian

Architecture by Peter Good-

fellowm

Find the right building materials is essential for birds building their nest. Birds can

spend a whole day in their quest for the building materials their structure needs. The

male bird chooses the location of the nest, and the female builds it. Their nests’ fea-

tures depend on the materials and techniques used in their construction. All building

materials for their architectural masterworks must be pliable and compressible.

A weaver bird collects the building materials. It will cut long strips from leaves or

extract the Mildrid from a fresh green leaf. The reason for choosing fresh leaves be-

cause the veins of dry leaves would be stiff and brittle, too difficult to bend, but fresh

-------------------------------------

Giovanni G. Bellani, Quand L’oiseau Fait Son Nid (When The Bird Makes Its

Nest) (Arthaud, 1996), p. 85-90.

ones make the work mush easier.

The weaver bird begins by tying the leaf fibers around

the twig of a tree. With its foot, it holds down one end

of the strip against the twig while taking the other end

in its beak. To prevent the entrance to the nest. Then it

uses its beak to weave the other fibers together. During

the weaving process, it must calculate the required

tension, because if it’s too weak, the nest will collapse.

The weaver bird won’t just begin building its nest, It

proceeds by calculating in advance what it needs to

do next - first, collecting the most suitable building

materials, then forming the entrance before going on

to build the walls. It knows perfectly well where to thin

or thicken the structure, and where to form a curve Its

behavior displays intelligence and skills.

I chose Baya Weaver as case for analyzing the con-

struction behavior and process.

/ 047RROJECT

NEST SITE SELECTION STRATEGIES

Tree height and size preference (7-9m, taller

and bigger) / Accessibility of nests by pred-

ator / Avoidance of high wind / Reduction in

the flying cost / The availability of nesting

materials and food / Surrounding biological

environment / Temperature / Light intensity /

Humidity / Rainfall ....

COLLECTING SUITABLE MATERIALS

Male Baya weavers need to collect thou-

sands of grass strands to build their nest. A

competition between them. The image shoes

the male weaver was pealing of a strand

from a palm tree, he was pealing of strands

only from a young leaf as it was easier to do

and more suitable raw materials for the nest.

BUILDING THE NEST

The male Baya Weaver builds the nest up to

the helmet stage, collecting materials and

weaving the pieces together. He then gets

his mate to approve the structure. Then the

final stage of building sees both adults par-

ticipating.

Left: Baya weaver bird nest

site. Photo by Sankrutyayan.

2012

Middle: Male Baya weaver

cllecting grass strands to

build their nests. Photo by

Atual Sinai Borke, 2012

Right: Female and male

Baya weavers b r ing ing

strips of grass blades to

constructing their nest.

Con t r i bu t ed b y Ca l v i n

Chang, 2010.

/ 049RROJECT

We are collaborating with mechanical students from Robotic

Automation Group for this design project. I am working with

Group 1 and Group 3. They are design 6-axis robotic arms with

A4 size working space. The expected goal is the two robotic

arms would collaborate and work together simultaneously.

However the final result is a little bit disappointing that I will

discussed them in detail in this chapter.

1.5 SIX-AXIS ROBOTIC ARMS

/ 051RROJECT

Group Three's robotic arm is made by black perspex, is one of

the most flexible and successable robots in the class. However,

they have relative serious issue in accuracy, they are quite shaky

during operation. This robotic arm is Arduino controlled. The

maximum weight to pick up is around 15 grams.

/ 053ROBOTICS

/ 055RROJECT

Group One's robotic arm is made by plywood. This is the version

two, the previous one was made by transparent perspex. This

robotic arms acts more stable than Group one. The end effector

is designed to have functions in picking up sticks and holding

pens / extruders to visualized the path. This robotic arm is

Arduino controlled. The maximum weight to pick up is around 15

grams.

1 servo HITEC HS-815BB

1 servo HITEC HS-755HB

2 servos HITEC HS-311

1 servo Tower pro 996R

1 micro servo Towe pro

The Arduino Controlled Dia-

gram provided by Evil Zoid

/ 057RROJECT

The assemble process of

Group One's robotic arms.

This is the version two as the

previous one was burned. The

new version is made by laser

cut plywood.

/ 059RROJECT

The prototype is simplied the environment by depth data,

balck area means inaccessible area, and white area means

easy accessible areas. Using 6-axis robots to simulation the

process and behavior in defining site locations, searching

suitable materials and assembling them in a relatively easy

logic. The materials has been simplied into 3 categories by

length. Type One with longest length has firest prority.

1.6 PROTOTYPE TESTING

ANALYZING AND DEFINING SITE

LOCATION

ENVIRONMENT ACCESSIBILITY

FLATNESS AREA

TO MATERIALS

RANGEI

RANGEII>

COLLECTING SUTIBALE MATERIALS /

SORTING

CONSTRUCTING

BUILDING ELEMENTS

SUITABLE

MATERIALS

NONSUTIABLE

MATERAISLS

TYPE A

TYPE B

TYPE C> >

ROBOTS ROBOTS

+

HUMAN

HUMAN

SIMGPLE LOGIC

/ 061RROJECT

ENVIRONMENT

+

MATERIALS

KINECT

OPENNI

OPENCV

Filtering environment by contrast / brightness /

threshold ...

BLOB SCANNER

PROC

ESSI

NG

PATH

FINDING

Defining site location by detecting the flatness

3D VISUAL

PLETHORA

3D Environment corrosponding to real

Site location

Detecting the centers and dimensions of materials, filtering useful materials

Sorting useful materials into three types by ranges of

dimensions

Sorting useful materials into three types by ranges of

dimensions

Type Adimension

range

Type B dimension

range

Type C dimension

range

Range Id = ?

Range IId = ?

Site boundaryOne location with a boundary (simple)

Multiple closed locations and various sizes of

boundaries make 'metaball'

/ 063RROJECT

DEFINING

A SITE

LOCATION

DEPTH IMAGE: site information

The depth image indicates the contour, where darker

color means more difficult to access to. I used this

depth image for analyzing the site location, and calcu-

lating the optimized path for searching materials later.

PSEUDO-CODE

opencv = new OpenCV ( this, image);

opencv.threshold(50);




OPENCV THRESHOLD: filtering site information

/ 065RROJECT

INACCESSIBLE AREA

The red areas represent inaccessible areas for search-

ing materials and calculating optimized path. They may

be areas that are too dangerous, too high or having

existing buildings on. In opposite, the orange areas

represent the suitable areas for site.

PSEUDO-CODE


fill (RED);


fill (ORANGE);

SUITABLE SITE LOCATION

/ 067RROJECT

SEARCHING

AND SORTING

MATERIALS

Material type one, type two, and type three (by length)

Distributing three types of materials on the physical

contour and detected by Kinect and filtered information

by depth / threshold

Library OpenNI;

PSEUDO-CODE:

simpleOpenNI context;

context = new SimpleOpenNI(this);

context.setMirror(true);

context.enableRGB();

context.update();

image(context.depthImage(), 0, 0);

image(context.rgbImage(), context.depthWidth() + 10,

0);

Detecting by Kinect

/ 069RROJECT

PHYSICAL CONTOUR: based on the threshold map

xx

PSEUDO-CODE


fill (RED);


fill (ORANGE);

FILTERING MATERIALS: detecting by kinect and filtering by threshold

/ 071RROJECT

Since the environment is detected by Kinect, there are

some small particles would be scanned into. These

small particles needed to be filtered first before any

calculation. In these case, particles with less than 50

pixels edge points are filtered. The “Blob Scanner”

Library in Processing is being used for this calculation.

PSEUDO-CODE

bs = new Detector (this, 255);

bs.imageFindBlobs (sticks);

bs.loadBlobsFeatures();

PVector [] edge = bs.getEdgePoints (sn);

point (edge [i].x, edge [i].y);

i++;

for (i<50) {

println(“STICK” + (sn+1) + “EDGE POINTS” +1);

/ 073RROJECT

Bounding Box of sticks before filtering small particles

The left image shows the bounding of materials after

filtering small particles with weight less than 100. The

right image indicates the range one and range two in

research, and all materials with centroid located within

range one.

Library: blobScanner

PSEUDO-CODE:

for (int i=0, i<bd.getBlobsNumber(); i++) {

if(bd.getBlobWeight(i)>100) {

if(dist(bd.getCentroidX(i), bd.getCentroidY(i),

site.x, site.y)<range1){

point(bd.getCentroidX(i), bd.getCentroidY(i));

bd.drawSelectBox(min, selectBoxColor, thickness);

bd.drawSelectContours(150, selectContourColor,

thickness);

}}}Bounding Box after filtering small particles

/ 075RROJECT

All suitable materials in range one (distance less than 200)

This step is to continue filtering materials to locate ma-

terials type one in range one, drawing with bounding

box and edges.

PSEUDO-CODE:

for (int i=0, i<bd.getBlobsNumber(); i++) {

if(bd.getBlobWeight(i)>400 &&

bd.getBlobWeight(i)<500 &&

bd.getLength(i)>200) {

if(dist(bd.getCentroidX(i), bd.getCentroidY(i),

site.x, site.y)<range1){

point(bd.getCentroidX(i), bd.getCentroidY(i));

bd.drawSelectBox(min, selectBoxColor, thickness);

bd.drawSelectContours(150, selectContourColor,

thickness);

}}}

Filtering materials by length and mass to defined material type one

/ 077RROJECT

Centroid coordinates of materials type one in range one

STICK 1 X:475 Y:124

STICK 2 X:561 Y:187

STICK 3 X:689 Y:193

STICK 4 X:743 Y:216

STICK 5 X:765 Y:252

STICK 6 X:555 Y:257

STICK 7 X:790 Y:269

STICK 8 X:505 Y:326

STICK 9 X:549 Y:365

STICK 10 X:671 Y:384

STICK 11 X:618 Y:418

STICK 12 X:537 Y:429

STICK 13 X:664 Y:446

STICK 14 X:534 Y:469

Get the coordinates of all material type one in range

one and output these coordrinates to A* path finding

algorithm as endNodes. Sorting the generated path

from shortest to longest which indicates the order for

searching. (More detail codes see Chapter 3)

Library: PathFinder

PSEUDO-CODE

text (bd.getCentroidX(i), bd.getCentroidY(i),);

GraphNode startNode;

GraphNode [] endNode;

void makeGraphFromDepthData (Graph,

backgroundImage, costImage, int tilesX, int tilesY);

void drawEdges();

void drawNodes();

void drawRoute();

A* path generated from site location to the selected materials location

/ 079RROJECT

Path Finding in 3D environment

The diagram indicates the calculation methodology of path-

finding in 3D environment.

PSEUDO-CODE

int cellSizeX;

int cellSizeY;

int dx = backImg.width / cellSizeX;

int dy = backImg.height / cellSizeY;

int col = backImg.get(dx,dy) & 0xFF;

int dz = col;

nodeID = cellSizeX *y +cellSizeX;

aNode = new GraphNode (nodeID, dx, dy, dz);

xCost = dx, yCost =dy, zCost = dz;

xzCost = sqrt (dx*dx + dz*dz);

yzCost = sqrt(dy*dy + dz*dz);

xyCost = sqrt(dx*dx + dy*dy);

xyzCost = sqrt(dx*dx + dy*dy + dz*dz);

xCost

yCost

dx

dydz

xyCost

xyzCost

/ 081RROJECT

1 2 3 4

7 8 9 10

13 14 15 16

19 20 21 22

5 6

11 12

17 18

23 24

Iterations showing

the logic of search-

ing and assembling.

/ 083RROJECT

Giving the coordi-

nates of material

location and site

location in order,

the robot arm works

continuously follow-

ing the order.

/ 085RROJECT

ASSEMBLE

MATERIALS

Red Arrow indicates At-

traction force; Blue Arrow

indicate Repelling force.

When the robots drop

the building elements,

these two force will be

applied to determine the

final outcome

When the site location

is more than one, and

these locations are rel-

atively close. Due to the

attraction and repelling

force, it will gradually

forming a ‘metaball’ like

shape

/ 087RROJECT

For Prototype One, the assembly logic is quite simple,

the picked materials will be distributed randomly in a

bounding shape. For this one, the longer sticks to be

selected first and then shorter sticks. So the bounding

shape is a cone-like shape. However, when I do the test

by robot, some sticks will falling down. So for next step,

I may need to detect the flatness or replace by some

other materials. And also make the construction more

complex and more interesting.

/ 091RROJECT

1 2 3 4

7 8 9 10

13 14 15 16

19 20 21 22

5 6

11 12

17 18

23 24

Iterations showing

the logic assem-

bling. The site loca-

tion increase from

one to four, assum-

ing the number of

robots increased

simultaneously.

/ 093RROJECT

/ 095RROJECT

/ 097RROJECT

/ 099RROJECT

In the future, applying in the earthquake site and other areas

after diasters, we can use behavior based walking mobiles

robots and flying mobile robots do the searching, sorting, and

assembling work. They have benefits in quike assembing, easy

operating and cheap cost.

More information about mobile robots please go to Chapter 2.4

& 2.5 in this book.

1.7 CRITICAL FUTURE

/ 101RROJECT

/ 103RROJECT

RESEARCH

The research for this project contains five parts: speculative design,

animal architecture, computation programming, artificial intelligence,

and robotics in architecture including theories and case studies.

2 / 105RESEARCH

xxxxxxxx

The research is mainly focus on the ideas from the book

Speculative Everything - Design, Fiction, and Social Dreaming

by Anthony Dunne & Fiona Raby and the book Design Futurin -

Sustainability, Ethics and New Practice by Tony Fry.

2.1 SPECULATIVE DESIGN

Dunne & Raby, from De-

signs for an Overpopulated

Planet, 2010.

/ 107RESEARCH

The cones present different kinds of potential future

(Stuart Candy, 2009)

Probable

Plausible futures (alternative future)

Possible

Intersects the probable and plausible (the preferable

future)

One role of designers is speculating how

things could be (speculative design),

this form of design aims to open up

new perspectives on wicked problems,

to create spaces for discussion and

debate about alternative ways of being,

and to inspire the encourage people’s

imaginations to flow freely. Design

speculations can act as a catalyst for

collectively redefining our relationship to

reality. Future is a medium to aid imag-

inative thought other than a destination.

Although the future is unpredictable,

we can help set in place today factors

that will increase the probability of more

desirable futures happening.

During 1980s design became hy-

per-commercialized and fully integrated

into the no-liberal model of capitalism

With the fall of the Berlin Wall in 1989

Marcel Wanders, Antelope,

designed for Bisazza, 2004.

Photograph by Ottavio To-

masini. Marcel decided the

surface of his holiday car

should be beautiful deep

shiny glass stones.

and the end of Cold War, alternative

models for society collapsed. Market-led

capitalism became one dimensional

with much less other possibilities or

alternatives.

The society has become more atomized

and individualized. The 20th century is

unsustainable.

But there is an opportunity currently

about alternative thinking to the current

system. We need more pluralism in

design, not of style but of ideology and

values.

------------------------------------------

Beyond Radical Design, Speculative

Everything- Design, Fiction, and Social

Dreaming, Anthony Dunne & Fiona Raby

/ 109RESEARCH

The Bouroullec Brothers’

Algue (2004) is using small

plastic, organic-looking

elements that can be linked

together to filter the light

and insulate or permeabilize

space through the assembly

of a module. The elements

such as a b io-morphic

pixel is made of a plastic

injection mold to reproduce

on a large scale like parts.

Algue thrive by following an

organic logic, addressing

architecture starting from

the millimeter.

To think as conceptual design is a place where many

interconnected and not well understood forms of de-

sign happen-speculative design, critical design, design

fiction, design futures, anti-design, radical design,

interrogative design, design for debate, adversarial

design, discursive design, futurescaping, and some de-

sign art. This separation from the marketplace creates

a parallel design channels free from market pressures

and available to explore ideas and issues.

What is potential to use the language of design to pose

questions, provoke, and inspire is conceptual design’s

defining feature. “Ideals are not measured by whether

they confirm to reality; reality is judged by whether

it lives up to ideals. Reason’s task is to deny that the

claims of experience are final and to push us to widen

the horizon of our experience by providing ideas that

experience ought to obey.” The ideal is a practical fic-

tion. Architecture has the richest, most diverse tradition

for exploring ideas of all the design disciplines.

Design exhibitions are moving beyond showcasing

designers and products to address more complex so-

cietal issues. Even though this kind of design activity

is difficult to finance but it is needed. It opens up new

possibilities not only for technology, materials, and

manufacturing but also for narrative, meaning, and the

rethinking of everyday life. Designers should focus on

society in the broadest sense other than just business.

----------------------------------------------------------

A Map of Unreality, Speculative Everything - Design,

Fiction, and Social Dreaming, Anthony Dunne & Fiona

Raby

/ 111RESEARCH

There are many possibilities socially engaged design for raising

awareness; satire and critique; inspiration, reflection, highbrow

entertainment; aesthetic explorations; speculation about possible

futures; and as a catalyst for change. Conceptual design can be

used as a form of critique.

Critical design is defined as “critical design uses speculative de-

sign proposals to challenge narrow assumptions, preconceptions,

and gives about the role products play in everyday life.” All good

design is critical. Critical design is critical thought translated into

materiality. It is about thinking through design. All good design

offers an alternative to how things are.

One purpose of critical design is to help us become more discerning

consumers, and to encourage people to demand more from industry

and society as critical consumers.

Critical design, by generating alternatives, can help people con-

struct compasses rather than maps for navigating new sets of

values.

---------------------------------------------------------------

Design as Critique, Speculative Everything - Design, Fiction, and

Social Dreaming, Anthony Dunne & Fiona Raby

Bernd Hopdengaertner’s

Belief System (2009). He

asked what would happen

if one of the tech industry’s

many dreams comes true,

if the tech make humans

machine readable were to

combine and move from lab

to everyday life.

Bernd Hopdengaertner’s

Belief System (2009). He

asked what would happen

if one of the tech industry’s

many dreams comes true,

if the tech make humans

machine readable were to

combine and move from lab

to everyday life.

/ 113RESEARCH

Speculative designs depend on dissemination and

engagement with a public or expert audience; they are

designed to circulate.

The project Between Reality and the Impossible for the

Saint Etienne International Design Biennale 2010 has

interested in how the relationship between the reality

of the here-and now and the fictional worlds alluded

to through props, atmosphere, supporting material,

staging, and so on can be managed. The intention

was to create a chain reaction starting from the initial

thoughts and ideas through the objects.

The starting point for this project Designs for an

Overpopulated Planet was a brief from Design Indaba

exploring the future of farming in the face of food

shortages. According to the UN we need to produce 70

percent more food in the next forty years. The current

situation is completely unsustainable. In 2050 the UN

predicts that the world population will be nine billionat.

They tend to build their own solutions, bottom-up, and

look at evolutionary processes and molecular technol-

ogies to explore how they could take control or evolu-

tion.

They believe there is tremendous value and potential

for design connecting with science about posible fu-

tures.

----------------------------------------------------------

Between Reality and the Impossible, Speculative Every-

thing - Design, Fiction, and Social Dreaming, Anthony

Dunne & Fiona Raby

Dunne & Raby, from Designs

for an Overpopulated Planet

Foragers, 2010.The Project

explores the future of

farming in the face of food

shortage, and explores how

we could take control or our

won evolution.

/ 115RESEARCH

Hummingbird nest, it is a

small cup shape with nar-

rowing bottom - cup mostly

dried grasses while bottom

mostly leaves. About 3 feet

off ground.

The research in animal architecture mainly focus on the

processes and behaviors of nest buildings of birds and social

insects like termites. The topics including behaviors of swarm

intelligence, emergent behaviors, stigmergy, single-minded, self-

organizing of birds and social insects. Espically I focues on the

research of bird nests from function to process and behaviors.

The main resource of the research materials from the book Bird

Nests and Construction Behavior by Mike Hansell and online

articles.

2.2 ANIMAL ARCHITECTURE

/ 117RESEARCH

SELECTION GATHERING ASSEMBLY

BIRD NEST

BUILDING

STAGES

BUILDING

COST

NAVIGATION

ABILITY

MATERIAL

SELECTION

TIME ENERGY

GATHERING TRANSPORTING ASSEMBLY LOAD OF MATERIALS

The intricate structure of

the minute sandgrain case

of the amoeba Difflugia

coronata demonstrates

that very simple organism

can show architectural

sophistication. (Photography

courtesy of Natural History

Museum).

A)SIMPLE MINDED

The principles for building stages are selection, gathering, and assembly.

Orderly outcomes can be the result of simple processes. Standard building

units, a repetitious assembly procedure and simple design rules produce

orderly structure. A honeybee comb is an impressive structure, but in for-

aging, bees how navigation skills, topographical learning and improvement

in handling of complex flower structure.

B) NO SPECIALIST ANATOMY

They used throughout their life on a daily basis. Three associated anatom-

ical features of birds as builders are: a delicate but strong instrument, the

beak, positioned close to the eyes, mounted on a very mobile neck.

C) TECHNIQUES SHAPE MATERIALS BUT MATERIALS SHAPE TECHNIQUES

Most basically, there are only two techniques, sculpting and assembly , and only three materials

animal,vegetable and mineral. Also concern building costs, navigation ability, specialization in

the selection of materials and choice of materials in relation to the size of the organism.

Building costs are measured as time (gathering/transportation/assemble) and energy (the load

of materials). They are keen to build near by the materials, and return to the material source

repeatedly. Some navigation skills and topographic memory abilities are further expectation.

Natural selection tends to favor specialist over generalists in the selection of building material.

The sale of the building units will also be appropriate to the size of the organism.

The structures built from top down need to prevent a structure from falling apart by bounding

together or sticking together. Self-secreted materials are not always glue or plastic materials,

they may be discrete, ready-made building units. Some building materials of animal origin are

created by species other than builders. Making a nest is making bits of material stay together

in a certain spatial relationship. Birds collectively make use of a wide variety of building materi-

als. Materials influence construction behavior and also shape the architecture of the nest itself.

The ambivalence of discussing whether construction should be complex, on one hand, regards

nest as remarkable structures, while on the other hand, categories the building behavior as

largely genetically determined and inflexible.

----------------------------------------------------------------------------------------------------

Construction, Bird Nests and Construction Behavior by Mike Hansell, 2000

/ 119RESEARCH

A fundamental distinction in nest building techniques is that

between sculpting and assembling (Hansell, 1984). Assem-

bly techniques can be divided into: pilling up, moulding,

sticking together, interlocking, sewing, and weaving. (Hansell,

1984) The purpose of these techniques is essentially two-

fold: to ensure that the nest stay attached to the nest site

and that the components of which it is made to do not fall

apart.

Birds do no have anatomy that is specialized for the build-

ing technique each shows. Building technique has little

relevance with birds’ beak, but strongly dependent upon

behavior. The nests can be constructed by whatever princi-

ples using a limited repertoire of stereotyped movements.

Stereotyped, repeated movements and simple building rules

can produce an elegantly simple or sophisticated structure when carried out

on standardized building material. This is the principle of brick wall. So much

depends on the careful choice or manufacture of building units and materials.

Velcro is now referred fastening for children’s clothing,because the attachment

principle is in the material not in the behavior. By contrast, tying shoelaces in a

landmark in a child’s development, and it is illustrate that weaving is the most

difficult nest building technique for birds (Howman & Begg, 1995). (pp.85)

Getting the nest started may require different rules, which allow the nest to be

fitted to the landscape. The obvious problem here is that the topography of the

nest site or geometry of its branch arrangement will not be entirely predictable

and may therefore require greater flexibility in the behavior than continuing

construction after a nest has been established. The added problem of getting

started is that of not having other nest materials to which to attached the cur-

rent beak load.

Figure: downy woodpecker nests a cavity carved into

a dead tree limb with a narrow entrance for limiting

access.

Sculptors, whether in trees or in the ground, illustrate

the power of a bird’s beak to excavate a cavity large

enough for the rearing of the young, and in the

subterranean species, digging a long burrow to give

them additional security.

Figure: The surface of mud nest of the cliff swallow

reveals the large number of mud pellets to build it up

The majority of birds that use this technique build with

mud. The only other bird nest material to be moulded

is salivary mucus,secreted by builders themselves.

This mucus, unmixed with other materials, is used to

construct the nest of the edible-nest swift-let, in which

the saliva is mixed with feathers.

Figure: The nest of the spotted dove is a platform of

twigs laid across one another.

SCULPTING MOULDING PILING UP

/ 121RESEARCH

Figure: Chimney swift makes a wall attached bracket

or straight twigs held together with salivary mucus.

Some swifts reinforce vegetation nests with mud. The

most architecturally satisfying example of the sticking

together technique is probably tan of the chimney

swift, a wall-attached bracket of straight twigs held

together with salivary mucus.

STICKING TOGETHER

WEAVING

Figure: The largely African weavers, are much smaller

birds, nests have a downward directed entrance.

Weavers starting a nest : woven structures bear loads

in tension and so the first strips must at least bear their

own weight and, secondly, the strips have no inherent

properties to secure them until tied to branches from

which the nest will be suspended. Spiral wrapping

round an attachment twig may give a strand temporary

stability, but it must be secured with a hitch or knot;

requiring integration of movements of beak and feet.

WEAVING

Figure: The nest of bushtit is a velcro fabric featuring

a characteristic lichen, which bears stiff projections,-

shown entangled with threads of spider cocoon silk.

There are three different construction methods are

recognized within this: entangle, stitches or pop-rivets

and velcro. Interlocking is possibly the most important

category of nest construction methods. -

INTERLOCKING

Figure: The nest of the striped tit-babbler is made of

broad strips of monocot leaf entangled.

The properties of the materials themselves combine

with the probing and binding behavior, entangling the

materials to give the nest its integrity. Construction with

plant materials, whether grass, bark or vine tendrils,

requires not only interlocking with the beak but, as the

materials accumulate, the shaping of a nest cavity to

hold the egg. This is achieved mainly with the breast

and legs.

INTERLOCKING | ENTANGLE

Figure: The nest of the rufous piha is an open-work

platform of stiff, interlocking vine tendrils.

This form of nest is made by linking together the

margin of green leaves attached to a shrub or bush by

means of fibrous stitches. The stitches are made by

driving the thread through the leaf, grasping it on the

other side and driving it through again. The coarseness

of the thread and the elasticity of the green leaf spring-

ing back to grip the thread passing through the hole

prevent the stitches from unraveling.

Figure: The gray-backed cameroptera attaches the in-

ner nest lining to the outer envelope of growing leaves

by driving though the leaf membrane.

It is the entanglement of vegetation in threads of silk.

All these have dry threads and so can only be used in

nest building as the looped material of a velcro fabric.

INTERLOCKING | VERLCOINTERLOCKING | STITCHES

/ 123RESEARCH

a) tree/brush; b) grass/reed;

c) ground; d) water;

e) ground/hole/cavity;

f) tree/hole/cavity;

g) wall; h) ledge

The outer nest layer is to make the nest

look different, implying that its function

is to make the nest less obvious to

visually hunting predators; however,

protection from water penetration and

temperature regulation are possible

alternative explanations. Some nests

are built with heads and tails. They are

functioned as bedchamber for male

birds, also act as false nests to distract

predators that have detected the nest.

Heads and tails appear to serve as

devices that distort or break up a typical

nest shape.

Nest attachment devices are solution

to problems of anchoring a nest in the

chosen nest site. (Diagrams on the

previous page showed different types of

nest attachments.)

Structural layer is the most important

layer that prevent from falling apart and

retaining the nest shape and integrity.

The structural layer of nest addresses

the problem of strength and cohesion in

the chosen nest site. Examination of the

major materials involved has shown that

there are certain identifiable material

solutions: silk and plant material to cre-

ate a velcro, flexible fibrous materials in

tension or compression, and beam cups

or platforms in compression. (pp.122)

Structural layer is the most important

layer that prevent from falling apart and

retaining the nest shape and integrity.

The structural layer of nest addresses

the problem of strength and cohesion in

the chosen nest site. Examination of the

major materials involved has shown that

there are certain identifiable material

solutions: silk and plant material to cre-

ate a velcro, flexible fibrous materials in

tension or compression, and beam cups

or platforms in compression. (pp.122)

/ 125RESEARCH

In this studio, we are using Open Source Java based Processing, Arduino, and Kinect.

Processing is a programming language, development environment, and online

community.

Arduino is an open source electronics platform based on easy-to-use hardware

and software. It’s intended for making interactive project. Arduino board senses the

environment by receiving inputs from many sensors, and affects its surroundings by

controlling lights, motors, and other actuators. Engineering students using Arduino

Due for their AI robots.

Kinect 360 is being used in this program. It is a line of motion sensing input device

by Microsoft for XBox 360. Based around a webcam-style add-on peripheral, it

enables users to control and interact with their computer.

2.3 COMPUTATION PROGRAMMING

Processing could work with Kinect

by using the Open Kinect library and

OpenNI library to detect the real world

environment and give continuous

feedback.

Processing working with Arduino

software and Arduino board to give data

to the robot.

Processing Website:

http://www.processing.org/

Arduino Website:

http://www.arduino.cc/

Kinect Website:

http://www.xbox.com/en-SG/Kinect/

/ 127RESEARCH

PATH FINDING ALGORITHM

Pathfinders let you plan ahead rather than waiting until

the last moment to discover there is a problem. A* is

the most popular choice for pathfinding, it’s fairly flex-

ible and can be used in a wide range of contexts. A*

was developed in 1968 to combine heuristic approach-

es like Greedy Best-First-Search and formal approach

like Dijsktra’s algorithm.

More detailing code about A* pathfinding go to Person-

al Learning Outcome

Pa t h f i n d i n g u s i n g A *

algorithm in Processing to

calculate optimized shortest

path from a start point to

one or multiple goals.

Path planning plays an important role in various fields

of application and research, computer games, virtual

environments, molecular biology and robotics.

Mobile robots are widely used in many hazardous

industrial fields where there may be dangers for

people, such as aerospace research, the nuclear

industry, and the mining industry. Path planning for a

mobile robot is to find a collision-free route, through

the robot’s environment with obstacles, from a

specified start location to a desired goad destination

while satisfying certain optimization criteria. Moreover,

to reduce the processing time, communication delay

and energy consumption the planned path is required

to be optimal with th shortest length.

Because the information of a dynamic environment

will change along with th movement of obstacles,

the complexity and uncertainty of the path planning

problem increase greatly in dynamic environment. The

A* algorithm is a path planning method to help the

robot to find the optimal path in grid decomposed static

maps. The environment with free space and obstacles

is presented by a set of uniformed regular grids. The

A* algorithm uses heuristic based Dijkstra algorithm to

obtain the optimal result of the robot.

(Configuration Space) The path planning problem is in

its most general form a geometric problem. It needs

four ingredients:

1. A description of the geometry of the mving entity (in

this called the robot)

2. A description of (the geometry of) the environment

in which the robot moves or operates (also called

workspace). The workspace contains obstaces.

3. A description of the degrees of freedom of the

robot’s motion.

4. A start and a goal configuration in the environment,

between which is a path is to be planned for the robot.

Comparing the general path

planning and optimized

path planning. Figures from

Amit’s A* Pages

/ 129RESEARCH

DIJKSTRA’S ALGORITHM GREEDY BEST-FIRST-SEARCH A* ALGORITHM

DIJKSTRA’S ALGORITHM

Dijkstra’s algorithm works by visiting vertices

in the graph starting with the object’s starting

point. It then repeatedly examines the closest

not-yet-examined vertex, adding its vertices

to the set of vertices to be examined. It ex-

pands outwards from the starting point until

it reaches the goal.

Dijkstra’s algorithm is guaranteed to find the

shortest path from the starting point to the

goal.

GREEDY BEST-FIRST-SEARCH

The Greedy Best-First-Search algorithm

works in a similar way, except that it has

some estimate (heuristic) of how far from the

goad any vertex is. Instead of selecting the

vertex closest to the starting point, it selects

the vertex closest to the goal.

Dijkstra’s algorithm is not guaranteed to find

the shortest path from the starting point to

the goal, but ti runs much quicker than Dijk-

stra’s algorithm because it uses the heuristic

function to guide its way towards the goad

very quickly.

A* ALGORITHM

A* was developed in 1968 to combine

heuristic approaches like Greedy Best-First-

Search and formal approaches like Dijkstra’s

algorithm. g(n) represents the exact cost of

the path from the starting point to any vertex

n, and h(n) represents the heuristic estimat-

ed cost from vertex to the goal. Each time

through the main loop, it examines the vertex

n that has the lowest f(n)=g(n)+h(n).

Dijkstra’s algorithm is guaranteed to find the

shortest path from the starting point to the

goal.

A* ALGORITHM

/ 131RESEARCH

ARDUINO DUE

The Arduino Due is a micro-controller board based

on the Atmel SAM3X8E ARM Cortex-M3 CPU. It

is the first Arduino board based on a 32-bit ARM

core microcontroller. It has 54 digital input/output

pins (of which 12 can be used as PWM outputs),

12 analog inputs, 4 UARTs (hardware serial ports),

a 84 MHz clock, an USB OTG capable connection,

2 DAC (digital to analog), 2 TWI, a power jack, an

SPI header, a JTAG header, a reset button and an

erase button. (Arduino website: http://arduino.cc/

en/Main/arduinoBoardDue)

The engineering group from Robotics Automation

used Arduino due as their micro-controller board

in their robot arm making.

KINECTOPEN KINECT / OPENNI

PROCESSINGARDUINO

ARDUINO DUE

6-AXIS ROBOT

HUMAN INTERACTION

ENVIRONMENT

/ 133RESEARCH

Harvard’s Micro Air Vehicles

Project inspired by the

biology of a bee and the

insect’s hive behavior. The

engineer team is working

to incorporate compact

high energy power sources

that make the tiny robots

capable of “ultra-low-power

computing” and contain

electronic ‘smart’ sensors.

The littles robots will use

refined ‘coordination algo-

rithms’ that can manage

mul t i p l e , i ndependent

machines.

An intelligent robot is a mechanical creature which can function

autonomously. "Function autonomously" indicates that the robot

can operate, self-contained, under all reasnable conditions

without requiring recourse to a human operator. Autonomy

means that a root can adapt to changes in its environment or

iteself and continue to reach its goal. (Robin R.Murphy, 2000)

The search on robotics in artificial intelligence focus on topics

including application on sensing, navigation, path planning, and

navigating with uncertainty.

2.4 ARTIFICIAL INTELLIGENCE

/ 135RESEARCH

Data acquisition

Filtering

Perception

Navigation

Localization

Decision Making

Locomotion

Kinematics

Motor Control

SENSE PLAN ACT

Andy Chang , A dvanced

Control& Robotics, National

Instruments Corp. The

makeup of simultaneous

localization and mapping,

o r SL AM , r ou t i nes fo r

robot navigation usually

involve combining mapping

techniques with ad-hoc

schemes using sensors to

react to the state of the

environment.

/ 137RESEARCH

ROBOT PATH PLANNING

ROBOT PATH PLANNING

IN STATIC ENVIRONMENT

ROBOT PATH PLANNING

IN DYNAMIC ENVIRONMENT

Robot Path Planning

in Know

Static Environment

Robot Path Planning

in Unknown

Static Environment

Robot Path Planning

in Know

Dynamic Environment

Robot Path Planning

in Unknown

Dynamic Environment

MOTION PLANNING is the ability for an agent to compute its own

motions in order to achieve certain goals. All autonomous robots

and digital actors should eventually have this ability.

GOALS

The goals for path planning for robots including compute mo-

tion strategies including geometric paths, time-parameterized

trajectories, and sequence of sensor-based motion commands;

achieve high-level goals including avoid collision with obstacles,

assemble/disassemble the engine, build a map of the hallway

and find and track the target.

CONSTRAINTS

Dealing with complex robots: multiple robots; movable objects;

non-holonomic & dynamic constraints; physical models and de-

formable objects; sensor-less motions; and uncertainty in control.

Dealing with complex environment: moving obstacles; and uncer-

tainty in sensing.

Dealing with complex objectives: optimal motion planning; inte-

gration of planning and control; assembly planning; and sending

the environment include model building and target finding /

tracking.

Khepera III mobile robot

approaching the designated

area of rock sampling. It is

running a Mobile-C agency

and is under the control

of a mobile agent with the

objectives of searching for

the sampling proper rocks.

/ 139RESEARCH

Michael Rubenstein, Christian Ahler

SWARM ROBOTICS, THE KILOBOT PROJECT

In current robotics research there is a

control methods for groups of decentral-

ized cooperating robots, called a swarm or

collective. These algorithms are generally

meant to control collectives of hundreds or

even thousands of robots. They need to be

cheap and easy to assemble and operate.

They can work together to complete a task

that is beyond the capabilities of any of its

individuals. Many such examples could be

found in nature: army ants and honeybee

colonies effectively forage over large areas

many kilometers wide; desert ant groups can

collectively transport large irregular objects

50 times their collective weight; termites

colonies construct mounds meters tall even

though individuals are only a few millimeters

tall themselves. These examples from nature

Up: Overview of the mobile

kilobots

Right: The reflection path

of robot communication

Isometric and bottom views

of Kilobot. Key features:

a) V ibrat ion motors; b)

Luthium-Ion batter y; c)

R ig id suppor t ing legs .

d) Infrared t ransmitter

receiver; e) Three-color

(RGB) LED, f ) Charging

tab, and g) Ambient light

sensor.

Left: Robot path following

have inspired long-standing research in collective ro-

botics to achieve parallelism, robustness and collective

capability of these natural systems.

The difficulty when using a simulation to validate an al-

gorithm for a collective of robots is the interaction with

each other, such as communication and sensing, and

with the environment such as movement and collisions.

To make a robot scalable to a large collective sizes, all

the operations of the robot must work on the collective

as a whole. The Kilobot robot has low cost ($14 worth

of parts) and quick assembly (5min) enable large num-

bers to be produced easily. They have abilities in differ-

ential drive locomotion, on-board computation power,

neighbor-to-neighbor distance sensing.

----------------------------------------

Michael Rubenstein, Christian Ahler, and Radhika

Nagpa . Kilobot: A Low Cost Scalable Robot System

/ 141RESEARCH

Sholomi Mir

SEED-PLANTING TUMBLEWEED ROBOT DRAWS FROM NA-

TURE TO FIGHT DESERTIFICATION

This tumbleweed-inspired robot that uses wind power to

study desertification and help scientists better understanding

the phenomenon. The round robot uses an internal fabric sail

stretched across a circular steel frame to roll across the terrain

and collect data about the formation of sand dunes, planting

seeds along the way. When there is no wind, the robot can lie

flat until the next gust picks up.

The Tumbleweed contains an onboard computer and a small

motor, which are powered by a kinetic generator. It is equipped

with an Arduino and Android-based core that allows it to use

GPS, transmit data, and collect climate information via a small

sensor. “There are applications where this system could go

where people cannot go or cannot afford to go, or cannot go

enough to collect this information that these researcher need.”

Announced by Mir. These wind powered robots, modeled after

tumbleweeds, are inexpensive alternatives to the rovers found

on Mars now.

Left: Tumbleweed robot

planting seeds along the

desert , the design was

inspired by tumbleweed

when building the robot.

Like tumbleweed the robot

is wind powered and helps

spread the seeds of plant-

life.

Right: the analysis diagram

of the robot in functions. W

/ 143RESEARCH

Robotics will have big impacts on the entire construction

industry over the next few years. Within the development of

digital architecture, the involvement of robotics in architecture

is opening up new aesthetic and functional potentials that could

change architectural design and building culture. The range

of robotic process is gradually explanding from prefabrication

towards direct use of robots on the construction site and

involving in desing process.

Research in robotics in achitecutre mainly including case

studeis of the industrial robots and mobiles robots application in

architecture field.

2.5 ROBOTICS IN ARCHITECTURE

Robot House, made by SCI-

Arc Students. The double-

h e i g h t 1 0 0 0 - s q u a r e -

f o o t Ro b o t H o u s e i s

a r e s e a r c h s p a c e f o r

hands-on col laborat ive

experimentation, advanced

multi-robotic platform,

a n d e x p l o r a t i o n a n d

architectural agency.

/ 145RESEARCH

Karola Dierichs, Tobias Schwinn, Achim Menges

ROBOTIC POURING OF FUNCTIONALLY GRADED

AGGREGATE STRUCTURE

Loose, designed macro-scale granulates can be used as

architectural materials system. Architecture is typically

conceptualized as one of the most permanent and stable

forms of human production. As a consequence it is com-

monly conceived as precisely planned, fully defined and

ordered in stable assemblies of material elements. But in

‘aggregate architecture’ , the elements are only in loose

frictional contact. If th individual grains are synthetically

produced, the resulting granular structures can be cal-

ibrated to suit specific architectural requirements, such

as structural and environmental performance. Designing

with these aggregate structures requires the architect to

observe the evolving formation rather than to precisely

define it (Dieriches and Menges, 2012).

Aggregates are defined as large amounts of elements in

loose contact (Cambou 1998; Duran 2000). In nature sand

or snow are considered granular or aggregate systems. The

Left: aggregate structure

consist ing of synthetic

macro-scale particles

Bottom: s ix-ax is robot

pouring designed granulates

using a magazine emitter-

head

Right: poured structure

u s i n g a l i n e a r K P L-

controlled pouring path /

Right bottom: responsive

motion-panning strategy for

online robot-control using

macro-scale non-convex

granulates

/ 147RESEARCH

L e f t : S i m u l a t i o n o f

H e x a p o d a l G r a n u l e s

Analyzing Joint Slips and

Contacts

Right: Particle Geometries

f o r M o u l d a n d S h e e t

Production

use of designed granulates that individual particle is customized to

meet specific architectural performance criteria such as frictional

interlocking or heat insulation (Hensel and Menges, 2006).

In this case study, a 6-axis robot is being used as a puring

device for designed aggregate structures both renders

the pouring process precise and offers the opportunity of

pouring patterns which are otherwise hard to achieve. In

pick-and-place robotics elements are individually positioned

in the overall structure in a very controlled manner.

(Bonwestsch, Gramazio and Kohler. 2007) In contrast,

robotic pouring aggregate formations are consequently

predictable only in terms of probability rather than

certainty. (p.197, Robotic Fabrication 2012). The additive

manufacturing such as fused deposition modeling (FDM)

(Oamn 2010) has a continuous stream of heated polymer

is extruded from an emitter head and deposited on a

height-adjustable printer-bed to form individual horizontal

layers. As the polymer cools down, the layer solidifies into

a permanent configuration and forms the basis for the next

layer.

/ 149RESEARCH

Howeler + Yoon Architecture & Squared Design Lab

ECO-PODS: CONCEPT STRUCTURE FOR BOSTON

This is a conceptual structure designed for Boston,

where an unfinished building would be covered in

modular pods growing algae for biofuel. The designers

intend to use the structure, called Eco-pods, to inform

the public about the potential of micro-algae, a bio-fuel

that can be grown vertically.

The pods would be continuously rearranged by robotic

arms (powered by the micro-algae produced) to ensure

the optimum growing conditions for algae in each pod.

The on-site robotic armature is designed to reconfigure

the modules to maximize algae growth conditions and

to accommodate evolving spatial and programmatic

conditions in real-time.

Left: Render Speculation

t h e p o d s w o u l d b e

continuously rearranged by

robotic arms to ensure the

optimum growing conditions

for alage in each pod.

R i g h t : T h e a s s e m b l e

d i ag rams ind i ca te the

flexibility in combination

/ 151RESEARCH

Gramazio & Kohler and Raffaello D’ Andrea in Coorpora-

tion with ETH Zurich

FLIGHT ASSEMBLED ARCHITECTURE

Flight Assembled Architecture is the first architectural

installation assembled by flying robots, free from the

touch of human hands. Fight Assembled Architecture

consists of over 1,500 modules which are placed by a

multitude of quafrotor helicopter, collaborating accord-

ing to mathematical algorithms that translate digital

design data to the behavior of the flying machines. The

flying vehicles, together, extends themselves as ‘living’

architectural machines and complete the composition

from their dynamic formation of movement and build-

ing performance. Within the build, an architectural

vision of a 600m high ‘vertical village’ for 30,000

inhabitants unfolds as model in 1:100 scale. The ideal

self-sustaining habitat that the authors pursue a rad-

ical new way of thinking and materializing vertical in

architecture.

Top: F ly ing robots can

operate freely in airspace

Le f t : F l y i ng r obo t s i n

working

Middle: The final prototype

1:100 scale

Right: The architectural

vision of vertical village for

30,000 inhabitants unfolds

locate at rural area of

Meuse, taking advantage of

an existing TGV connection

/ 153RESEARCH

Scientists from Harvard University and the Wyss Institute

SELF-ORGANIZING ROBOT ANTS

They are as industrious as Bob the Builder and possess the same

social intelligence as a colony of termites. They can build model

towers, castles and pyramids without supervision.

The robots can act very similar way that of te termites. The ter-

mites are working on local information rather than a central orga-

nization. Termites can build structures of several meters without

requiring a coordinated strategy. Thy use very simple intructions

provided by their peers and the environment to know where to

put the next piece of the mound and finally build a mound adapt-

ed to their environment. This use of local information is called

stigmergy.

Termes bots are guided by singals from infrared and ultrasound

sensors. Each termes bots are given an overall idea what the

finished job should look like before being left to get on with it,

research said. They also know when to lift a building brick and

where to attach it, as well as how to avoid collisions and even

how to reach higher levels by constructing staircases.

Left: Termites inspired

robots

Bottom: a) Inspi red by

termites moulds b) Termites

are working in building

c) robots working d) The

robots can build model

towers, astels and pyramids

without supervision.

/ 155RESEARCH

PERSONAL LEARNING OUTCOME

This part mainly contains personal learning outcome in Processing,

Arduino, Kinect that relating to the prototype of this project.

3 / 157

EMERGENT BEHAVIOR WITH ATTRACTION AND REPULSION FORCE ArrayList <Agent> agents;

ArrayList <Vec3D> totTail;

PointOctree octree;

float clipRadius = 40;

//attractor and repellors

Vec3D repeller = new Vec3D(100,400,0);

Vec3D repeller2 = new Vec3D(300,100,0);

Vec3D seekTarget = new Vec3D(200, 300, 0);

Vec3D seekTarget2 = new Vec3D(100, 200, 0);

Vec3D seekTarget3 = new Vec3D(400,400,0);

//behavior variables

int population = 500;

float maxVel = 2;

float wandertheta = 1;

float futLocMag = 10;

float tailViewAngle = 60;

float tailCohMag = 0.5;

float tailCohViewRange = 20;

float tailSepMag = 3;

float tailSepViewRange = 5;

float att = 1;

float rep = 5;

float maxAttract = 0.1;

float maxRepel = 1;

-----------------------------------------------

void setup() {

background(220);

size(500, 500, P2D);

agents = new ArrayList();

totTail = new ArrayList <Vec3D>();

for (int i=0; i < population; i++) {

Vec3D origin = new Vec3D (random

(width), random(height), 0);

Agent myAgent = new Agent (origin);

agents.add(myAgent);

}}

-----------------------------------------------

void draw() {

background(220, 254);

smooth();

//CALL FUNCTIONALITY

for (Agent Ag : agents) {

Ag.run();

totTail.addAll(Ag.tail);

Ag.tailSeek(totTail);

}

totTail.clear();

// draw repeller

pushStyle();

noStroke();

fill(0, 200, 200,100);

rectMode(CENTER);

rect(repeller.x, repeller.y, 50, 50);

rect(repeller2.x,repeller2.y,100,100);

popStyle();

//draw attractor

float ampA = 10;

pushStyle();

for (int i = 0 ; i < ampA ; i++) {

noFill();

strokeWeight(1);

stroke(0, 200, 0, map(i, 0, ampA, 255, 0));

ellipseMode(CENTER);

ellipse(seekTarget.x, seekTarget.y, i*15, i*15);

ellipse(seekTarget2.x, seekTarget2.y, i*10, i*10);

ellipse(seekTarget3.x,seekTarget3.y,i*5,i*5);

}

popStyle();

}

-----------------------------------------------------------

// CLASS AGENTS

class Agent {

Vec3D loc = new Vec3D(0, 0, 0);

Vec3D speed = new Vec3D(random(-20, 20), ran-

dom(-20, 20), 0); //re-map the contour??

Vec3D acc = new Vec3D();

ArrayList <Vec3D> tail = new ArrayList <Vec3D> ();

int Tcount = 0;

int TLen = 20;

int TStep = 6;

/ 159

//AGENTS

float angle;

float VAngle;

Vec3D perip = new Vec3D();

//TAILS

float tailAngle;

float tailVAngle;

Vec3D tailPerip = new Vec3D();

//FUTURE LOCATIONS

Vec3D FutVec;

Vec3D FutLoc;

//CONSTRUCTOR

Agent(Vec3D loc_) {

loc = loc_;

}

----------------------------------------------------------

// RUN THE BEHAVIORS OF THE AGENTS

void run() {

display();

move();

border();

drawTail();

FutLoc();

tailVAngle = radians(tailViewAngle);

if (appWander) wander();

repel(repeller);

repel(repeller2);

seek(seekTarget);

seek(seekTarget2);

seek(seekTarget3);

}

-----------------------------------------------------

// SEEK

void tailSeek(ArrayList<Vec3D> flowfield) {

tailSeparate(tailSepMag, tailSepViewRange,

flowfield);

tailCohesion(tailCohMag, tailCohViewRange,

flowfield);

}

-----------------------------------------------------

// COHESION

-----------------------------------------------------

// TAIL COHESION

void tailCohesion(float magnitude, float range,

ArrayList <Vec3D> flowfield) {

Vec3D sum = new Vec3D();

Vec3D steer = new Vec3D();

int count = 0;

for (int i = 0; i < flowfield.size();i++) {

float distance = FutLoc.distanceTo(flowfield.

get(i));

if (distance > 0 && distance < range) {

tailPerip = (flowfield.get(i)).sub(loc);

tailAngle = tailPerip.angleBetween(speed,

true);

if (tailAngle < 0) tailAngle += TWO_PI;

if (abs(tailAngle) < tailVAngle ) {

sum.addSelf(flowfield.get(i));

count++;

}

}

}

if (count>0) {

sum.scaleSelf(1.0/count);

steer = sum.sub(loc);

//steer.normalize();

steer.scaleSelf(magnitude);

acc.addSelf(steer);

}

}

----------------------------------------------------------

//TAIL SEPARATE STEER

void tailSeparate(float magnitude, float range, ArrayList

<Vec3D> flowfield) {

Vec3D steer = new Vec3D();

int count = 0;

for (int i = 0; i < flowfield.size();i++) {

float distance = FutLoc.distanceTo(flowfield.get(i));

if (distance > 0 && distance < range) {

tailPerip = (flowfield.get(i)).sub(loc);

tailAngle = tailPerip.angleBetween(speed,

true);

if (tailAngle < 0) tailAngle += TWO_PI;

if (abs(tailAngle) < tailVAngle ) {

Vec3D diff = loc.sub(flowfield.get(i));

diff.normalizeTo(1.0/distance);

steer.addSelf(diff);

count++;

}

}

}

if (count > 0) {

steer.scaleSelf(1.0/count);

}

//steer.normalize();

steer.scaleSelf(magnitude);

acc.addSelf(steer);

}

-----------------------------------------------------

// BOUNDARY

void border() {

if (loc.x > width) {

//loc.x -=width;

speed.x = speed.x * -1;

}

if (loc.x < 0) {

//loc.x+=width;

speed.x = speed.x * -1;

}

if (loc.y > height) {

//loc.y-=height;

speed.y = speed.y * -1;

}

if (loc.y < 0) {

//loc.y+=height;

speed.y = speed.y * -1;

}

}

-----------------------------------------------

// MOVING

/ 161

void move() {

speed.addSelf(acc);

speed.limit(maxVel);

loc.addSelf(speed);

acc.clear();

}

-----------------------------------------------------

// AGENT DISPLAY

void display() {

strokeWeight(random(1,3));

stroke(0);

point(loc.x, loc.y, 0);

}

-----------------------------------------------------

// DRAW TAIL

void drawTail() {

Tcount++;

if (Tcount > TStep) {

tail.add(loc.copy());

Tcount = 0;

}

if (tail.size() > TLen) {

tail.remove(0);

}

for ( int i = 1; i < tail.size();i++ ) {

Vec3D a = tail.get(i-1);

Vec3D b = tail.get(i);

if (a.distanceTo(b) < 30) {

stroke(0, 0, 0, map(i, 0, tail.size(), 0, 100));

strokeWeight(map(i, 0, tail.size(), 0.5, 1));

line(a.x, a.y, b.x, b.y);

}

-----------------------------------------------------

// FUTURE LOCATION

void FutLoc() {

FutVec = speed.copy();

FutVec.normalize();

FutVec.scaleSelf(futLocMag);

FutLoc = FutVec.addSelf(loc);

stroke(50, 100);

strokeWeight(1);

if (futPrev) line(loc.x, loc.y, FutLoc.x, FutLoc.y);

}

----------------------------------------------------

// WANDER BEHAVIOR

void wander() {

float wanderR = 50;

float wanderD = 80;

float change = 5;

wandertheta += random(-change, change);

Vec3D circleLoc = speed.copy();

circleLoc.normalize();

circleLoc.scaleSelf(wanderD);

circleLoc.addSelf(loc);

Vec3D circleOffSet = new Vec3D(noise(wan-

derR*cos(wandertheta)), noise(wanderR*sin(wan-

dertheta)), 0);

Vec3D target = circleLoc.addSelf(circleOffSet);

Vec3D steer = target.sub(loc);

steer.normalize();

steer.scaleSelf(1);

acc.addSelf(steer);

}

----------------------------------------------------

// SEEK (ATTRACTORS)

void seek(Vec3D target) {

float distanceT = target.distanceTo(loc);

if (distanceT > 0 && distanceT < 800) {

Vec3D desired = target.sub(loc);

desired.normalize();

desired.scaleSelf(att);

Vec3D steerTarget = desired.sub(speed);

steerTarget.limit(maxAttract);

acc.addSelf(steerTarget);

}

}

----------------------------------------------------

// REPELLING FORCE

void repel(Vec3D target) {

float distanceT = target.distanceTo(loc);

if (distanceT > 0 && distanceT < 150) {

Vec3D desired = target.sub(loc);

desired.normalize();

desired.scaleSelf(rep);

Vec3D steerTarget = desired.sub(speed);

steerTarget.limit(maxRepel);

steerTarget.scaleSelf(-1);

acc.addSelf(steerTarget);

}

}

}

/ 163

import pathfinder.*;

Graph gs = new Graph();

PImage graphImage; // visible image

PImage costImg; // cost image

int start, end;

int numTilesX, numTilesY;

GraphNode[] gNodes, p;

GraphEdge[] gEdges, exploredEdges;

// Pathfinder algorithm

IGraphSearch pathFinder;

// Used to indicate the start and end nodes

as selected by the user.

GraphNode startNode, endNode;

// store paths and color

ArrayList<GraphNode[]> paths;

ArrayList<Integer> pathColor;

long time; // used for performance stats

boolean ready = false;

------------------------------------------

PATH FINDING USING A* BASED ON DEPTH DATA IN 2D ENVIRONMENT

void setup(){

size(640, 640);

cursor(CROSS);

smooth();


// import depth data ( image/ video/ kinect)

graphImage = loadImage(“map1a.png”);

costImg = loadImage(“map1b.png”);

gs = new Graph();

numTilesX = numTilesY = 40;

makeGraphFromBWimage(gs, graphImage,

costImg, numTilesX, numTilesY, true);

// Get arrays of nodes and edges

gNodes = gs.getNodeArray();

gEdges = gs.getAllEdgeArray();

// Create a path finder object

pathFinder = makePathFinder(gs);

paths = new ArrayList<GraphNode[]>();

pathColor = new ArrayList<Integer>();

}

-----------------------------------------------

void draw(){

background(0);

display();

}

-----------------------------------------------

IGraphSearch makePathFinder(Graph graph){

IGraphSearch pf = null;

float f = 2.0f;

pf = new GraphSearch_Astar(gs, new Ash-

CrowFlight(f));

return pf;

}

GraphNode[] usePathFinder(IGraphSearch pf)

{

time = System.nanoTime();

pf.search(start, end, true);

time = System.nanoTime() - time;

p = pf.getRoute();

exploredEdges = pf.getExaminedEdges();

showStats();

return p;

}

------------------------------------------

// Visualise the algorithm and path, draw

route if end nodes are selected

void chooseRoute() {

stroke(255, 0, 0);

strokeWeight(1.5f);

if(endNode != null)

line(startNode.xf(), startNode.yf(), end-

Node.xf(), endNode.yf());

else

line(startNode.xf(), startNode.yf(), mouseX,

mouseY);

}

// Display search analysis data

void showStats() {

println(“No. edges examined: “ + explored-

Edges.length);

/ 165

pr in t ln (“Analys is t ime: “ + ( t ime *

0.000001f));

println();

}

-----------------------------------------------

// Graph drawing functions, to draw Nodes

and Edges

void drawNodes(){

pushStyle();

noStroke();

fill(255);

for(GraphNode node : gNodes)

ellipse(node.xf(), node.yf(), 2, 2);

popStyle();

}

void drawEdges(GraphEdge[] edges, int line-

Col, float sWeight){

if(edges != null){

pushStyle();

noFill();

stroke(lineCol);

strokeWeight(sWeight);

for(GraphEdge ge : edges)

line(ge.from().xf(), ge.from().yf(), ge.to().

xf(), ge.to().yf());

popStyle();

}

}

// Draw Routes

void drawRoute(GraphNode[] r, int lineCol,

float sWeight){

if(r.length >= 2){

pushStyle();

stroke(lineCol);

strokeWeight(sWeight);

noFill();

for(int i = 1; i < r.length; i++)

line(r[i-1].xf(), r[i-1].yf(), r[i].xf(), r[i].yf());

// Route start node

strokeWeight(0.0f);

fill(0, 0, 255);

ellipse(r[0].xf(), r[0].yf(), 5, 5);

// Route end node

fill(255, 0, 0);

ellipse(r[r.length-1].xf(), r[r.length-1].yf(), 5, 5);

popStyle();

}

}

-----------------------------------------------

// the shortest path is calculated by A* Algo-

rithm

void makeGraphFromBWimage(Graph g,

PImage backImg, PImage costImg, int tilesX,

int tilesY, boolean allowDiagonals){

int dx = backImg.width / tilesX;

int dy = backImg.height / tilesY;

int sx = dx / 2, sy = dy / 2;

// use deltaX to avoid horizontal wrap around

edges

int deltaX = tilesX + 1; // must be > tilesX

float hCost = dx, vCost = dy;

float dCost = sqrt(dx*dx + dy*dy);

float cost = 0;

int px, py, nodeID, col;

GraphNode aNode;

py = sy;

for(int y = 0; y < tilesY ; y++){

nodeID = deltaX * y + deltaX;

px = sx;

for(int x = 0; x < tilesX; x++){

// Calculate the cost based on depth data

if(costImg == null){

col = backImg.get(px, py) & 0xFF;

cost = 1;

}

else {

col = costImg.get(px, py) & 0xFF;

cost = 1.0f + (256.0f - col)/ 16.0f;

}

// If col is not black then create the node and

edges, black indicates inaccessbile areas.

if(col != 0){

aNode = new GraphNode(nodeID, px, py);

g.addNode(aNode);

if(x > 0){

g.addEdge(nodeID, nodeID - 1, hCost * cost);

if(allowDiagonals){

g.addEdge(nodeID, nodeID - deltaX - 1, dCost * cost);

g.addEdge(nodeID, nodeID + deltaX - 1, dCost * cost);

}

}

if(x < tilesX -1){

g.addEdge(nodeID, nodeID + 1, hCost * cost);

if(allowDiagonals){

g.addEdge(nodeID, nodeID - deltaX + 1, dCost * cost);

g.addEdge(nodeID, nodeID + deltaX + 1, dCost * cost);

}

}

if(y > 0)

g.addEdge(nodeID, nodeID - deltaX, vCost * cost);

if(y < tilesY - 1)

g.addEdge(nodeID, nodeID + deltaX,

vCost * cost);

}

px += dx;

nodeID++;

}

py += dy;

}

}

-----------------------------------------------

// Display the calculated edges, and nodes

void display() {

if(graphImage != null)

image(graphImage, 0, 0);

drawEdges(exploredEdges, color(255, 255,

255, 100), 1.0f);

drawNodes();

if(ready)

for(int i = 0; i < paths.size(); i++)

/ 167

drawRoute(paths.get(i), pathColor.get(i),

2.5f); // draw all ready paths, use new color

for each

// show mouse-controlled start/end selection

if(mousePressed == true) {

if(startNode != null)

chooseRoute();

}

}

-----------------------------------------------

// visualize the path in processing with

mouse controlled

public void mousePressed(){

noCursor();

if (paths.isEmpty()) {

startNode = gs.getNodeAt(mouseX, mous-

eY, 0, 16.0f);

} else {

startNode = endNode;

}

}

public void mouseDragged(){

endNode = gs.getNodeAt(mouseX, mouseY,

0, 16.0f);

}

public void mouseReleased(){

cursor();

if(endNode!= null && startNode != null &&

startNode != endNode){

start = startNode.id();

end = endNode.id();

GraphNode[] p = usePathFinder(path-

Finder);

paths.add(p);

ready = true; // report that the route is

ready

pathColor.add(color(random(255), ran-

dom(255), random(255)));

}

}

CONVERT 2D DEPTH DATA INTO 3D MESH USING PELTHORA LIBRARY

CONVERT 2D DEPTH DATA INTO 3D MESH USING PELTHORA LIBRARY import toxi.processing.*;

import processing.opengl.*;

import plethora.core.*;

import toxi.geom.*;

import peasy.*;

PeasyCam cam;

Ple_Terrain pTer;

float [][] heights;

int DIMX = 400;

int DIMY = 400;

int col = 20;

int row = 20;

void setup(){

size(800, 600, OPENGL); //OR p3d?

smooth();


cam = new PeasyCam(this, 0,0,0,800);

//declare a vector as the location

Vec3D location = new Vec3D(0,0,0);

pTer = new Ple_Terrain(this, location,

col,row, DIMX/col,DIMY/row);

//generate a data-map from a depth image

and load that information into the height of

the terrain

heights = pTer.loadImageToBuffer(“map1c.

png”);

pTer.loadBufferasHeight(heights, 0 , 100);

}

void draw() {

background(0);

stroke(0,90);

strokeWeight(2);

pTer.display();

stroke(255,140,0,140);

strokeWeight(1);

pTer.drawLines(true,true,true); //horizontal,

/ vertica / diagonal / all

}

/ 169

//CHANGE CODE FROM PATH FINDING IN 2D

ENVIRONMENT FROM makeGraphFromB-

Wimage:

void makeGraphFromBWimage(Graph g,

PImage backImg, PImage costImg,

int cellSizeX, int cellSizeY, boolean allowDiag-

onals){

cellSizeX = cellSizeY = 20;

int dx = backImg.width / cellSizeX;

int dy = backImg.height / cellSizeY;

int deltaX = cellSizeX+ 1;

float xCost = dx, yCost = dy;

float zCost, xzCost, yzCost, xyCost, xyz-

Cost;

float cost = 0.0;

int px, py, nodeID, col;

float pz, dz;

GraphNode aNode;

py = dy;

for(int y = 0; y < cellSizeY ; y++){

PATH FINDING USING A* BASED ON DEPTH DATA IN 3D ENVIRONMENT

nodeID = deltaX * y + deltaX;

px = dx;

for(int x = 0; x < cellSizeX; x++){

if(costImg == null){

col = backImg.get(px, py) & 0xFF;

pz = dz = col;

cost = 1;

}

else {

col = costImg.get(px, py) & 0xFF;

pz = dz = map(col, 0,255, 0, 100); //

remap the height to 1~100

}

if(col != 0){

xCost = dx;

yCost = dy;

zCost = dz;

xzCost = sqrt (dx*dx + dz*dz);

yzCost = sqrt(dy*dy + dz*dz);

xyCost = sqrt(dx*dx + dy*dy);

xyzCost = sqrt(dx*dx + dy*dy + dz-

*dz);

aNode = new GraphNode(nodeID, px,

py, pz);

g.addNode(aNode);

if(x > 0){

g.addEdge(nodeID, nodeID - 1, xz-

Cost * cost);

if(allowDiagonals){

g.addEdge(nodeID, nodeID - deltaX

- 1, xyzCost * cost);

g.addEdge(nodeID, nodeID + deltaX

- 1, xyzCost * cost);

}

}

if(x < cellSizeX -1){

g.addEdge(nodeID, nodeID + 1, xz-

Cost * cost);

if(allowDiagonals){

g.addEdge(nodeID, nodeID - deltaX

+ 1, xyzCost * cost);

g.addEdge(nodeID, nodeID + deltaX

+ 1, xyzCost * cost);

}

}

if(y > 0)

g.addEdge(nodeID, nodeID - deltaX,

yzCost * cost);

if(y < cellSizeY - 1)

g.addEdge(nodeID, nodeID + deltaX,

yzCost * cost);

}

px += dx;

nodeID++;

}

py += dy;

}

}

/ 171

REFERENCES

0.2 BACKGROUND IMAGES &FIGURES

Soft Structures http://www.expandedenvironment.org/soft-structures/ EXTS

Termites Mould http://www.touringaustralia.de/Animals/Termites.php

Stone Sprey http://www.massmarket.tv/6275/we-like-stone-spray/

Nest Selection in Weaver Birds. http://micusp.elicorpora.info/search/viewPaper/BIO.

G0.09.1.pdf

Studies on Nest-Site Selection by the Baya Weaver http://www.idosi.org/wjz/

wjz4(4)2009/11.pdf

1.2 UNPREDICTABLE TEXTS

Deadliest earthquakes and tsunamis of the past century http://en.tengrinews.kz/

opinion/334/

Haitai Earthquake Faces and Figures http://www.dec.org.uk/haiti-earthquake-facts-

and-figures

1.2 UNPREDICTABLE ENVIRONMENT IMAGES

Earthquake magnitudes http://www.expandedenvironment.org/soft-structures/ EXTS

Unrescued Living http://www.telegraph.co.uk/news/picturegalleries/world-

news/2662401/Chinese-earthquake-aftermath.html?image=2

Haiti Shelter http://www.emilytroutman.com/index.php#mi=2&pt=1&pi=10000&s=

11&p=2&a=0&at=0

Haiti shelter https://www.flickr.com/photos/un_photo/4276934309/in/gallery-cmck-

ane-72157623219576268/

Japanese Disaster Relief Project for Earthquake http://www.shigerubanarchitects.

com/SBA_NEWS/SBA_news_5.htm

Sleep Box in Japan http://www.theguardian.com/world/2009/apr/09/berlus-

coni-camping-comment-earthquake

Recycled cardboard paper make shelter http://biginjapan.com.au/2011/10/shige-

ru-ban-giving-shelter/

Sichuan tent-school http://sn.ifeng.com/jiaoyu/detail_2013_04/22/734528_0.shtml

Sichuan temporary settlement http://blog.salvationarmyusa.org/2013/04/22/salva-

tion-army-responds-to-sichuan-earthquake/

Chile tent http://www.e-architect.co.uk/chile/chile-earthquake-rebuilding

Tent city in San Gregorio http://www.theguardian.com/world/2009/apr/09/berlus-

REFERENCE

coni-camping-comment-earthquake

Potential Using Materials http://sherpas2.blogs.sapo.pt/389774.html

Proposed Houseing http://ikeda-lab.sfc.keio.ac.jp/home/en/project/2011_bub-

ble-dome

Earthquake resistant housing made by container http://activerain.trulia.com/blogs-

view/3511013/affordable--earthquake---hurricaine-resistant-shipping-contain-

er-home

ReCover Accordion Shelter http://inhabitat.com/emergency-shelters-and-disaster-

relief-for-the-people-of-haiti/

Calearth Disaster Resistant Housing http://inhabitat.com/emergency-shelters-and-

disaster-relief-for-the-people-of-haiti/

1.3 BUILD BY WASTE TEXT

Baya Weaver nest selection http://www.cyclists.in/photo/baya-weaver-bird-nests

Baya Weaver collecting material http://wildabs.com/birds/male-baya-weaver-collect-

ing-nesting-material

Bay Weaver constructing nests http://www.besgroup.org/2010/05/29/baya-weav-

er-completing-nest/

1.3 BUILD BY WASTE IMAGES & FIGURES

Recycled Windshield Greenhouse, http://inhabitat.com/recycled-windshield-green-

house-grows-more-glass/

Ball-shaped Shelter. http://inhabitat.com/5-brilliant-backyard-sheds-built-from-recy-

cled-materials/6-best-curious-tiny-sheds-from-random-materials-4/?extend=1

Sound Wave. http://forum.xcitefun.net/the-creation-recycled-sculptures-t43862.html

To Live. http://forum.xcitefun.net/the-creation-recycled-sculptures-t43862.html

Building with Pop Cans, http://inspirationalvillage.me/tag/recycled-materials/

Built by recycled bottles. http://www.ecofriend.com/eco-friendly-materials-sustain-

able-buildings.html

Building by 7000 Recycled Phone Books. http://inhabitat.com/amazing-building-

made-from-7000-recycled-phone-books/

Temporary shelter built by soap cans. http://www.greendiary.com/2011-eco-friend-

ly-homes-built-recycled-material.html

Micro-Financed Straw House. http://www.greendiary.com/2011-eco-friend-

ly-homes-built-recycled-material.html

Plastic Frantastic http://knowledge.allianz.com/environment/energy/?722/incredi-

ble-buildings-made-from-recycled-materials-gallery

Turning waste into building blocks of the future city. http://archinect.com/news/arti-

cle/76898650/turning-waste-into-building-blocks-of-the-future-city

/ 173

Cover 10-Storey Building with 1,000 Recycled Doors. South Korean artist Choi

Jeong-Hwa. http://www.ecologyrunner.com/2012/01/artist-covers-10-storey-build-

ing-with.html

The Big Church, http://inhabitat.com/the-big-crunch-raumlabor-creates-an-incredi-

ble-building-from-discarded-materials/

Earth Shape Building http://bc-interior.blogspot.com.au/2010/09/earthship-building-

going-up-in-south.html

1.4 LEARNING FROM ANIMAL IMAGES & FIGURES

Representation of the process of Baltimore oriole nest construction in Avian Architec-

ture by Peter Goodfellowm Princeton University Press 2011. P.103

Baya Weaver Bird Nests http://www.cyclists.in/photo/baya-weaver-bird-nests

1.5 SIX-AXIS ROBOTICSW

2.2 ANIMAL ARCHITECTURE IMAGES AND FIGURES

Hummingbird Nests http://folkwaysnotebook.blogspot.com.au/2013/02/un-

known-winter-birdnest.html

2.3 COMPUTATION PROGRAMMING IMAGES AND FIGURES

Amit’s A* Pages: http://theory.stanford.edu/~amitp/GameProgramming/index.html

2.4 ARTIFICIAL INTELLIGENCE IMAGES AND FIGURES

Harvard’s Micro Air Vehicles Project http://www.topsecretwriters.com/2014/01/

as-bees-go-extinct-harvard-develops-a-robotic-alternative/

Mapping and Localization (SLAM) http://machinedesign.com/motion-control/mo-

bile-manipulators-go-mainstream

2.4 ARTIFICIAL INTELLIGENCE TEXTS

William Regli, Robot Path Planning http://www.docstoc.com/docs/117197100/Ro-

bot-Lab-Robot-Path-Planning

Khepera III mobile robots http://www.mobilec.org/apps/vision/

Rumbleweed Robot Planting Seeds Along the desert http://www.thevoltreport.com/

tumbleweed-robot-planting-seeds-along-the-desert/

2.5 ROBOTICS IN ARCHITECTURE v

Robot House http://kree8tiv.blogspot.com.au/2013/02/sci-arc-students-explore-

future-of.html

Robotic Pouring of Graded Aggregate Structure http://icd.uni-stuttgart.de/?p=10339

Eco-Pods http://www.dezeen.com/2009/10/02/eco-pods-by-howeler-yoon-architec-

tureand-squared-design-lab/

Flight Assembled Architecture http://www.gramaziokohler.com/web/e/projekte/209.

html

Robot ANT http://www.dailymail.co.uk/sciencetech/article-2558666/Rise-ANT-

BOTS-Amazing-robots-behave-like-termites-operate-build-small-structures-

WITHOUT-instructions.html, http://www.mono-live.com/2014/02/robots-ter-

mites-who-work-by-coordinating.html

Books

Dunne, Anthony, and Fiona Raby (2013). Speculative Everything: Design, Fiction, and

Social Dreaming (Cambridge, MA: MIT Press): design of ideas and possible futures

Fry, Tony (2008). Design Futuring: Sustainability, Ethics and New Practice (Oxford:

Berg): new challenges for design, the need to change

Wood, John (2007). Design for Micro-Utopias: Making the Unthinkable Possible (Al-

dershot: Gower): metadesign, design narratives

Weinstock, Michael (2010). The Architecture of Emergence: The Evolution of Form in

Nature and Civilisation (Chichester: Wiley): an overview of nature-inspired approach-

es and project examples you can use as benchmarks (the Introduction is in the Drop-

box).

Hensel, Michael, Achim Menges, and Michael Weinstock, eds (2004). Emergence:

Morphogenetic Design Strategies, Architectural Design (London: Wiley) | AD 2006 - 2

(76) Techniques and Technologies in Morphogenetic Design | AD 2012 - 2 (82) Ma-

terial Computation - Higher Integration in Morphogenetic Design: these three issues

of AD focus on emergence and natural prototypes.

Hansell, Michael H. (2000). Bird Nests and Construction Behaviour (Cambridge; New

York: Cambridge University Press): an academic book focusing on nests

Hansell, Michael H. (2007). Built by Animals: The Natural History of Animal Architec-

ture (Oxford: Oxford University Press): a popular book with an overview of all animal

architecture

Shiffman, Daniel (2008). Learning Processing: A Beginner’s Guide to Programming

Images, Animation, and Interaction (Amsterdam; Boston: Morgan Kaufmann; Elsevi-

er): introduction to programming

Bohnacker, Hartmut, Benedikt Gross, Julia Laub, and Claudius Lazzeroni (2012

[2010]). Generative Design: Visualize, Program, and Create with Processing (New

York: Princeton Architectural Press): an excellent reference resource.

Blum, Jeremy (2013). Exploring Arduino: Tools and Techniques for Engineering Wiz-

ardy (Indianapolis, IN: Wiley): a good general introduction to Arduino and electronics

Shiffman, Daniel (2011). The Nature of Code (New York: Daniel Shiffman): overview

of nature-inspired

Craig, John J. (2005 [1986]). Introduction to Robotics: Mechanics and Control, 3rd

International edn (Upper Saddle River, NJ; London: Pearson Prentice Hall): a textbook

explaining low-level control principles

/ 175

Murphy, Robin (2000). Introduction to AI robotics (Cambridge, MA: MIT Press): a text-

book introducing concepts of intelligent robotics

Melgar, Enrique Ramos, Ciriaco Castro Diez, and Przemek Jaworski (2012). Arduino

and Kinect Projects: Design, Build, Blow Their Minds (New York: Apress): introduction

to Kinect and a variety of project including a Kinect-driven drawing robot

Gertz, Emily, and Patrick Di Justo (2012). Environmental Monitoring with Arduino (Se-

bastopol, CA:O’Reilly): approaches to environmental monitoring – a source of ideas

and possible extensions

Igoe, Tom (2011 [2007]). Making Things Talk, 2nd edn (Beijing; Farnham: O’Reilly):

communication between devices using Arduino – a source for further ideas

Brell-Çokcan, Sigrid and Johannes Braumann, eds (2013). Rob|Arch 2012: Robotic

Fabrication in Architecture, Art, and Design (Wien: Springer-Verlag): conference pro-

ceedings with a variety of projects

McGee, Wes and Monica Ponce de Leon, eds (2014). Robotic Fabrication in Architec-

ture, Art and Design 2014 (Cham: Springer): conference proceedings with a variety

of projects

Gramazio, Fabio and Matthias Kohler, eds (2014). Made by Robots: Challenging

Architecture at a Larger Scale (Chichester: Wiley): issue of AD with an overview of

robots in architecture

Video

The Nature of Code on Vimeo: video lecture and tutorials supporting the book

The Nature of Code in Python for Grasshopper: video tutorials

Tutorial Series for Arduino, by Jeremy Blum: introductory series of video tutorials that

covers materials in the book.

Plethora Project Video tutorials, Season 1: Introduction to Processing

APPENDICES

The appendices include movie scripts for mid-term prototype (around

3 minutes) and final presentation (around 10 minutes).

PROTOTYPE ONE

JUAN YANG

SONY PMW-EX1

20/09/2014 01 11 :)

Prototype One Filming

3min20second

Filmic, Above Ground

Part one is to demonstrate the movement and rotation

of the robot.

Part two is to simulate how robot works for researching

and assembling the materials.

Part three is to show the pictures of final outcomes.

Key Issues of this movie:

The lighting was not set up properly, so the background

looks dark and not consistent. TheA reason may also

be not setting up proper white balance point when

using Sony-CAM.

It is not very smooth when scaling up and down. I need

to practice more for next movie shooting.

NAME

DURATION

BACKGROUND MUSIC

CONTENT

THINGS NEED TO IMPROVE

/ 181

PROTOTYPE FINAL

JUAN YANG

SONY PMW-EX1

24/10/2014 02 23

Final Filming

10min20second

Filmic, Above Ground

Overall Review, explain the thesis (and statement)

Background Content: earthquake site, building by

waste materials, design speculation in both

Prototype from defining site location, to searching suit-

able materials and planning optimized path, and finally

assembly.

Future Scenario: different types of mobiles robots will

be applied in the future speculation design.

NAME

DURATION

BACKGROUND MUSIC

CONTENT

/ 189

Design Thesis "Building Like Animals- using autonomous robotics to search, evaluate and build"

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