ABSTRACT
This chapter considers the trajectory tracking task, in which the tracking of both pose and velocities are required with time constraints. It presents a visual trajectory tracking control strategy for nonholonomic mobile robots. A trifocal tensor based visual control strategy is proposed to regulate a mobile robot to track the desired trajectory expressed by a set of pre-recorded images in large workspace. Trifocal tensor among three views is exploited to obtain the orientation and scaled position information, which is used for geometric reconstruction. To compensate for the unknown depth and extrinsic parameters, an adaptive controller is developed using Lyapunov-based method, achieving asymptotic tracking with respect to the desired trajectory. An adaptive controller is developed considering the unknown depth and extrinsic parameters, and asymptotical convergence is guaranteed for almost all practical circumstances including both tracking and regulation tasks based on Lyapunov analysis.
