A 3-level adaptive robust control strategy for autonomous mobile robots

This paper presents a three level adaptive robust control strategy for wheeled mobile robots (WMR) that provides a WMR the ability to move to targets in a known environment with the shortest path while avoiding obstacles. Specifically, in the upper-level, an improved binary tree algorithm is used to plan the shortest path to the targets with obstacle avoidances. In the middle-level, the desired forward and steering velocities that enable stable tacking of the planned path are synthesized based on the kinematic model of the WMR with the consideration of non-holonomic constrains. In the lower-level, based on the physical modeling and system identification of the WMR dynamics, an adaptive robust control (ARC) algorithm is developed to make sure that the WMR can actually deliver the desired velocities for path tracking even in the presence of parametric uncertainties and uncertain nonlinearities such as unknown friction disturbances and modeling errors. Comparative experimental results are also obtained to verify the effectiveness of the proposed control strategy in actual implementation.