Visual Guidance of Robotic Wheelchair

(Mohammed Arab Boadher)

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Abstract

Most of the research effort in the visual guidance of autonomous robotic wheelchairs have been devoted to road edge detection. However, less attention has been paid to the after-detection process, especially the physical interpretation of what had been detected. In fact, there is a wide gap between the scene model built based on image processing algorithms and the physical model of the environment where the robotic wheelchair progresses. In this paper, we investigate the interaction between the scene model and the world model, and we propose a visual control scheme for robot guidance that minimizes the model error induced by processing raw image data. The involved control system includes the fuzzy approach at two levels: a fuzzy perception system which detects efficiently the road edges from the perception-domain image, and a fuzzy control system which uses the knowledge base information and the scene model to control the robot motion. On the other hand, the fuzzy control system is finely tuned through feed-backing mean square errors between the scene model parameters and the knowledge-base data. Hence, a road configuration from a preprocessed image is compared with a fuzzy template made from the fuzzy membership function based on the knowledge base module. Finally, the fuzzy controller as tuned is used to home the robot on the planned path. This paper shows the principle of this system and the simulation experiment results confirming the feasibility of the approach. Keywords: Fuzzy Control, Vision System, Road Edge Detection, Visual Navigation, Robotic wheelchair.
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