Experimental Motion Planning and Control for an Autonomous Nonholonomic Mobile Robot

This paper presents an architecture for the navigation of an autonomous mobile robot evolving in an uncertain environment with obstacles. The proposed strategy consists in separating the path planning from the control algorithm. The path planning is done by computing the time optimal collision-free trajectory which takes into account the limitations on the linear and angular speeds of the vehicle. The position and shape of obstacles are computed by a vision algorithm using a single camera. A saturated controller based on integral sliding mode is designed to solve the tracking problem in the presence of input saturations and of the unknown disturbances. The effectiveness, perfect performance of obstacle avoidance, real-time and high robustness properties are demonstrated by experimental results.