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Static and Dynamic Obstacle Avoidance Behaviour for Powered Wheelchair Control System

WORLD CONGRESS ON INDUSTRIAL AUTOMATION 2015. Static and Dynamic Obstacle Avoidance Behaviour for Powered Wheelchair Control System. Presenter : Jaya Bhanu Rao Supervisor : Dr. John Hedley Date : 20 July 2015. Introduction.

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Static and Dynamic Obstacle Avoidance Behaviour for Powered Wheelchair Control System

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  1. WORLD CONGRESS ON INDUSTRIAL AUTOMATION 2015 Static and Dynamic Obstacle Avoidance Behaviour for Powered Wheelchair Control System Presenter : Jaya Bhanu Rao Supervisor : Dr. John Hedley Date : 20 July 2015 Newcastle University

  2. Introduction • Disabled or elderly people unable to manoeuvre powered wheelchair smoothly due to frail and lack of dexterity in handling joystick movement. • Leads to fatigue and discomfort to wheelchair users. • Smooth wheelchair movement and transition are needed to overcome this problem. Newcastle University

  3. Objectives • To develop a robust algorithm to detect and avoid static and dynamic obstacles. • To develop a control system which can assist the wheelchair user in minimising the sharp shifting of wheelchair movement. • To validate wheelchair navigation via joystick using Matlab and Player/Stage simulation on Ubuntu 12.04LTS platform. Newcastle University

  4. Wheelchair Control Architecture Newcastle University

  5. Laser Data Clustering Point distance based segmentation (PBDS) K.Rebai et. al. 2009 Newcastle University

  6. Laser Data Clustering Newcastle University

  7. Collision Avoidance • Collision avoidance can be divided into static and dynamic obstacle. These obstacles can be avoided with collision avoidance behaviour which is based upon VO method and Collision Cone principle. Fiorini and Shiller, 1998; Chakravarthy and Ghose, 1998 Newcastle University

  8. Static Obstacle Avoidance Newcastle University

  9. Dynamic Obstacle Avoidance Newcastle University

  10. Emergency Stop Behaviour The inputs of the emergency stop behaviour include the sensor data and the maximum weight of the wheelchair speed. This behaviour becomes active if the minimum distance to the obstacle is below a minimum specific threshold or the maximum weight of the robot velocity is zero. Newcastle University

  11. Fuzzy Inference System for Obstacle Avoidance Behaviour Newcastle University

  12. FISInput/Output Newcastle University

  13. Performance Metrics Ceballos et al., 2010 Newcastle University

  14. Performance Metrics Newcastle University

  15. Results Newcastle University

  16. Conclusion • Based on the simulated results it have been proven that there was a significant improvement in the wheelchair movement with Fuzzy Inference System. • Further work will be carried out to introduce other behaviours and to further improve the performance of the system. Newcastle University

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