Introduction to Problem based Learning – The AAU Way

1

Introduction to Problem based Learning – The AAU Way

Program:• Monday : Structure, teaching task's,

courses,

• Tuesday : The Aalborg model - trying it out, PBL/Project Work and Assessment

• Wednesday : Supervision

Coffee break's at ap. 10.00 and 14.00 - Lunch at 12.00

2

Introduction to Problem based Learning – The AAU Way

Program for to day, Structure, teaching task's, courses :

• Welcome• Introduction and short presentation • Structure and conditions• Teaching task's• Courses• Exercises

3

Structure of Aalborg University

Welcome toAalborg University

4


University SenateRectorate

Faculty of Humanities

Faculty of Engi-neering and Sc.

Faculty of Social Science

DepartmentsStudy

Programmes

5

• Secretary and labs• Research• Teaching






Institute of Elec-tronic Systems

StudyProgrammes

6

• Project work• Course activities

• Secretary and labs• Research• Teaching






Institute of Elec-tronic Systems

Computer Eng.Electronic and .

7

Working tasks for VIP’s

Professor Associated Professor

Assistent Professor

Ph.D.

student

Research 40% 40% 45% 83%

Teaching 60% 60% 55% 17%

Teaching

In hours

497 h 497 h 456 h 140 h

8

Study board for Electronics and Information Technology

9

Controlling the studies

Study Regulations:

• General regulations

10


Study Regulations:


• Sector’s, lines or specialization’s– Objectives and content

4.6. INTELLIGENT AUTONOMOUS SYSTEMS

Objectives and contents of the specialisation

The objectives of the specialisation in Intelligent Autonomous Systems are summarised as follows:

to provide students with knowledge in modelling of mechanical systems such as spacecraft, ships, and mobile robots, enable the student to apply modern methods of control to problems related to autonomous systems, to analyse methods of state observation, parameter estimation and sensor fusion in mechanical systems, to provide students with a comprehension of supervisory control, fault-tolerant control and fault detection, to let students analyse software architectures for autonomous systems.

The courses include necessary general theoretical topics within process control forautonomous systems but modules are also made available in scientific communication and proficiency in English language for those who need it.

11


Study Regulations:



• Specific semesters– Theme

SPRING Semester – Intelligent Autonomous SystemsTHEME: Modelling and ControlPERIOD: 1 February - 30 June PURPOSE: To give knowledge and comprehension of optimal and robust control theory. To give the students the ability to analyse modern control methods for multi input/multi output systems. To give students the ability to apply modelling methods and control synthesis for advanced mechanical systems.CONTENTS: The project is based on a problem of control and supervision of an autonomous system. The model of the mechanical system has to be derived. The vital part of the project is the choice of the set of actuators and sensors for onboard application. Different control strategies have to be investigated and compared. The supervisor system responsible for autonomy onboard has to be designed. The chosen solution has to be implemented on a real time platform and tested, either by the computer simulations or dedicated hardware.COURSES: Courses will be given in the field of modelling of mechanical systems, supervisory andfault tolerant control, and modern control theory. EXAM: The external oral examination is based on the prepared project documentation. Each student is marked according to the 13-scale.

12


Study Regulations:



• Specific semesters– Theme– Projects

Model based tracking for navigation

Background As part of an ongoing research project (with Computer Science AAU and The Danish Institute of Agricultural Sciences) an autonomous vehicle is developed which navigates autonomously in the field. The aim is to reduce the inputs to the field and monitor the growth of the individual plants, thereby providing obvious environmental and economic advantages over more traditional farming.

PurposeIt is important in such applications to both navigate accurately in the field but also to be able to identify individual plants. The aim in this project is to use perspective images captures from a camera mounted on the front of the vehicle to provide estimates of structure of the crop rows as well as position of the individual plants. The focus will not be on the image analysis but on sensor fusion with non-vision sensors mounted on the vehicle e.g. wheel encoders, differential GPS as well as integration of information about the known structure of the field.The aim is to use all available information on the autonomous vehicle in order to achieve the best possible estimates of the vehicle and individual plant position (in the order of cm).

MethodsThe project will include:•Modeling of vehicle system and plant pattern in the camera image •Prediction of the crop structure based on the system models as well as previous measurements (images anddata from sensors) •Estimation of vehicle position and orientation as well as plant position •Algorithms are simulated in the laboratory on simple setup. •If possible the algorithms are applied to data acquired in the field.

13


Study Regulations:



• Specific semesters– Theme– Projects– Courses

Study related courses (SE):

Fault Detection and Automated SystemsModelling of Mechanical SystemsController StructuresModelling of Mechanical Systems IIEngineering Responsibilities

Project related courses (PE):

Robust ControlOptimal ControlSupervisory ControlNeural Networks and Fuzzy LogicProject Management and Team Building

14


Study Regulations:



• Specific semesters– Theme– Projects– Courses– Semester group

15

Teaching task’s

Project

Project courses lectures seminar

Study courses and lectures

Examination

Examination

50% - 33%

50% - 67%

Lecturer/instructor

Lecturer/instructor

Supervisor: Advisor and facilitator

Examinor/censor

Examinor

Structure of a semester:

16

Courses

• Description

Course DescriptionOptimal Control TheoryPurpose:

To give the students knowledge in optimal control and practical experience with optimal control strategies based on minimisation of a performance index.

Contents: Dynamic programming LQ control Introduction of reference and disturbance conditions Introduction of integral conditions Use of observer, LQG control The position of closed loop poles Prerequisites: Analogue and Digital Control (FP6-4, PR6-1, PR6-2), Stochastic systems (FP6-3, FP8-5)

Duration: 1 module Category: Project theme course (PE- course)

17

Courses

• Description

• Placed in a timetable for the semester

20

Courses

• Description

• Placed in a timetable for the semester

• Syllabus

21

Courses

Each lesson/lecture (Mini module):• Duration 3 hours 45 minutes (½ day)• 2 lectures app. 45 min each• Exercises in groups, app. 2 hours

– The lecturer is now instructor

The purpose of the combination of lectures/exercises is to increase the comprehension of the curriculum

22

Courses

What kind of exercises would you chose?

• Promote comprehension and methodical ness

How will you act as instructor during the exercises in the groups?

• Ask questions about how they have made their solution

• Make sure that they have understood the basic principles of the problems

23

Courses

Differences between project course (PE) and study course (SE)

• Examination– PE has no formal examination by the lecturer, it is

examined during the project examination by the supervisor

– SE is examined by the lecturer, normally as a written examination (passed/non passed)

• Exercises– PE is used in the project, exercises is examples– In SE the student must learn to solve examination

exercises

24

Lunch until 12.45

25

Course exercise

• Think of an engineering subject you all know something about

• Suppose that you have to do a course on that subject

• Make a short exercise that will learn the students the major point of a specific part of your course

26

Course exercise continued

For one group at a time do:

• Give your exercise to the other three groups who starts solving it

• Prepare how you will instruct the groups during their problem solving

• After 5-10 minutes of problem solving 2 persons from your group enters each of the other groups and starts acting as an instructor

Introduction to Problem based Learning – The AAU Way

Documents

Transcript of Introduction to Problem based Learning – The AAU Way