Visual Servoing Trajectory Tracking of Nonholonomic Mobile Robots Without Direct Position Measurement

Abstract

Localization is one of the most difficult and costly problems in mobile robotics. To avoid this problem, this paper presents a new controller for the trajectory tracking of nonholonomic mobile robots using visual feedback without direct position measurement. This controller works on the basis of a novel adaptive algorithm for estimating the global position of the mobile robot online using natural visual features measured by a vision system and its orientation and velocity measured by odometry and Attitude and Heading Reference System (IMU&Compass) sensors. The nonholonomic motion constraint of mobile robots is fully taken into account, compared with most of the existing visual servo controllers for mobile robots. The Lyapunov theory is used to prove that the proposed adaptive visual servo controller gives rise to asymptotic tracking of a desired trajectory and convergence of the position estimation to the actual position. A graphical processing unit is adopted to implement the proposed adaptive controller in parallel to achieve real-time detection and tracking of visual features. Experiments on a mobile robot are conducted to validate the effectiveness and robust performance of the proposed controller.