Vision-based tracking control of nonholonomic mobile robots without position measurement

Localization is one of the most crucial and difficult problems for motion control of mobile robots despite of tremendous research efforts made for years. This paper presents a new vision-based controller for controlling a nonholonomic mobile robot to track a desired trajectory without directly measuring its position. A novel adaptive estimator is embedded into this new controller to estimate global position of the mobile robot online using natural visual features measured by a vision system, and its orientation and velocity measured by odometry/inertia/magnetic sensors. It is proved by Lyapunov theory that the proposed controller gives rise to asymptotic tracking of a desired trajectory and convergence of the position estimation to the actual position. The experiment is conducted to validate the proposed controller.