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Construction and Motion control of a mobile

robot using Visual Roadmap

By: Harshad SawhneyGuide: Dr. Amitabha Mukerjee

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Objective

Source

Destination

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Introduction

• Inspiration From Human Brain.• The roadmap approach, captures connectivity

of robot’s free space.• 3-DOF mobile robot constructed.

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Construction Of Robot

• Major Components:

Microcontroller Arduino

Wireless module Xbee

Motor driver2 DC motors

Lithium-Ion battery

Image Source: robokits.co.in

Receives Data

UART communication

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Camera Input

Image Processing

Wireless data transfer

Microcontroller receives

command

µC sends output

Robot Advances

Destination Reached

Flow Chart of Robot Navigation

NO

Stop

YES

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Image Pre-processing

• 10k images taken.• Background subtraction performed.• Parameters extracted - robot navigation.

Few images from dataset

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Initial Image Background subtraction

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Distance Metric Computation

• L2-norm expansion method.• Dist(X, Y) = sqrt(||X||2 + ||Y||2 - 2*||Y’X||)

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Graph generation

• k-nearest neighbours calculated.• Robot location as nodes.• k=6 taken.• k=10 ; robot jumps larger distance.

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Nearest nodes to some vertices

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Shortest path calculation1. Without Obstacles: – Dijkstra’s algorithm used.

Shortest Path Graph

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Shortest path calculation

1. With obstacles:– Obstacles image extracted.– Compared the image with the dataset.– Nodes and edges removed.– Reduced to no obstacles case.

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Obstacle Image

Image of environment with obstacles Obstacle image extraction

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Shortest path calculation

Shortest Path Graph with obstacles in the environment

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Robot Motion Control

• Feed the nodes.• Camera: Negative closed loop feedback

mechanism.• Reach till destination.• Real Time.

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Algorithm for controlling robot

• (x, y, Ɵ): Robot current parameters• (x’, y’, Ɵ’): Node parameters• Ɵ : Robot vector angle.• Ɵ1 : Position of robot and node vector angle.

• Step1: Ƒ = | Ɵ - Ɵ1 |• Rotate till | Ƒ | < ɛ• Step 2: Move till | (x-x’)2+ (y-y’)2|< ɛ1

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Algorithm for controlling robot

• Step 3: Align till | Ɵ - Ɵ’| < ɛ2

• Steps executed in increasing order of priority.• Thus, the camera provides negative feedback

closed loop system.

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Results

• Robot accurately navigates.• Videos demonstrating robot navigation.

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Challenges

• Distance metric computation: limits sampling density.

• Real time motion: possibly leading to collisions.

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Future Work

• Dynamic obstacle avoidance• Update graph first time; use relative changes

in image for future considerations.

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References

[1] Amitabha Mukerjee, M Seetha Ramaiah, Sadbodh Sharma, Arindam Chakraborty, “The Baby at One Month: Visuo-motor discovery in the infant robot".[2] Joshua B. Tenenbaum, Vin de Silva, John C. Langford, “A Global Geometric Framework for Nonlinear Dimensionality Reduction", 2000.[3] Jean-Claude Latombe, "Robot Motion Planning”, Edition en anglais. Springer, 1990.[4] Choset, Howie, Principles of robot motion: theory, algorithms, and implementations. MIT press, 2005.[5] Seth Hutchinson, Gregory D Hager, and Peter I Corke. A tutorial on visual servo control. Robotics and Automation, IEEE Transactions on, 12(5):651{670, 1996.