Adaptive trajectory tracking control of a wheeled mobile robot via Lyapunov techniques

This paper develops the control methodologies under the specific assumption of the data source environments, for trajectory tracking of a wheeled mobile robot (WMR) with vision data. To solve the problem of trajectory tracking control of WMR, one novel kinematics control law is presented to steer the vehicle to asymptotically follow the desired trajectories. To compensate for dynamic effects associated with the dynamic models, an adaptive nonlinear trajectory tracking control law is presented to ensure asymptotic trajectory tracking for the vehicle. The experimental system is composed of a wireless RS232 modem, a digital signal processor (DSP), a wheeled mobile robot, and a vision system with a host computer. A computation-effective and high-performance controller using the digital signal processor is constructed for executing the developed sophisticated trajectory tracking laws. Simulation and experimental results are included to illustrate the feasibility and effectiveness of the proposed control method.