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Construction and Motion control of a mobile robot using Visual Roadmap

Construction and Motion control of a mobile robot using Visual Roadmap. By: Harshad Sawhney Guide: Dr. Amitabha Mukerjee. Objective. Source. Destination. Introduction. Inspiration From Human Brain. The roadmap approach, captures connectivity of robot’s free space.

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Construction and Motion control of a mobile robot using Visual Roadmap

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  1. Construction and Motion control of a mobilerobot using Visual Roadmap By: HarshadSawhney Guide: Dr. AmitabhaMukerjee

  2. Objective Source Destination

  3. Introduction • Inspiration From Human Brain. • The roadmap approach, captures connectivity of robot’s free space. • 3-DOF mobile robot constructed.

  4. Construction Of Robot Receives Data UART communication Lithium-Ion battery Wireless module Xbee • Microcontroller Arduino 2 DC motors Motor driver Image Source: robokits.co.in Major Components:

  5. Flow Chart of Robot Navigation NO YES Stop

  6. Image Pre-processing • 10k images taken. • Background subtraction performed. • Parameters extracted - robot navigation. Few images from dataset

  7. Initial Image Background subtraction

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

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

  10. Nearest nodes to some vertices

  11. Shortest path calculation • Without Obstacles: • Dijkstra’s algorithm used. Shortest Path Graph

  12. Shortest path calculation • With obstacles: • Obstacles image extracted. • Compared the image with the dataset. • Nodes and edges removed. • Reduced to no obstacles case.

  13. Obstacle Image Image of environment with obstacles Obstacle image extraction

  14. Shortest path calculation Shortest Path Graph with obstacles in the environment

  15. Robot Motion Control • Feed the nodes. • Camera: Negative closed loop feedback mechanism. • Reach till destination. • Real Time.

  16. 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

  17. 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.

  18. Results • Robot accurately navigates. • Videos demonstrating robot navigation.

  19. Challenges • Distance metric computation: limits sampling density. • Real time motion: possibly leading to collisions.

  20. Future Work • Dynamic obstacle avoidance • Update graph first time; use relative changes in image for future considerations.

  21. References [1] AmitabhaMukerjee, M SeethaRamaiah, Sadbodh Sharma, ArindamChakraborty, “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.

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