Trajectory Tracking of Nonholonomic Mobile Robots Using a Vision-based Adaptive Algorithm for Position and Velocity Estimation

Abstract One difficult issue for trajectory tracking control of nonholonomic mobile robots is measurements of the robot's position and linear velocity. To solve this problem, this paper presents a new controller to control a nonholonomic mobile robot to trace a desired trajectory using an omnidirectional vision system and inertial sensors without measuring the robot's position and linear velocity. Based on a new projection model of the omnidirectional vision system, a novel adaptive estimator is developed and embedded into the new controller for estimating the position and linear velocity of the robot on-line using the continuously tracked natural feature points in the omnidirectional image sequence, the robot's acceleration and orientation measured by the inertial sensors. It is proved by Lyapunov theory that the proposed controller gives rise to asymptotic tracking of a desired trajectory and convergence of the estimations of the robot's position and linear velocity to their true values. Experiments were conducted to validate the superior performance of the proposed adaptive controller.