Dynamic visual servoing of mobile robots based on learning control inputs

Abstract

In this paper, a precise trajectory tracking method for mobile robot using a vision system is presented. In solving the problem of precise trajectory tracking, a hierarchical control structure is used which is composed of a path planer, vision system, and dynamic controller. When designing the dynamic controller, non-ideal conditions such as parameter variation, frictional force and external disturbance, are considered. The proposed controller can learn bounded control input for repetitive or periodic dynamics compensation which provides robust and adaptive learning capability. Moreover, the vision system allows the robot to compensate the cumulative location error which exists when a relative sensor, like encoder, is used to locate the robot. The effectiveness of the proposed control scheme is shown through experiment as well as computer simulation.