Human-robot interaction is one of the most basic requirements for service robots. In order to provide the desired service, these robots are required to detect and track people in human cluttered environment. This book presents a novel approach for classifying a target person in a crowded environment. The system used the approach of Hough transform for human detection using camera mounted on wheelchair. Using data from Hough transform our system classifies the target person from other human beings in the environment. Our system tracks human being by gathering details of his position and velocity, and then converting this data into corresponding linear and angular velocity of wheelchair. System used in the project is an intelligent wheelchair with partial AI and partial human command based working architecture with LRF and stereo camera mounted on it. It works on a Linux OS and uses robot operating system (ROS) for the operation of the wheelchair. Our approach is feasible for mobile robots with an identical device arrangement.

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