Runhua Wang, Zhejin Zhu, Xuebo Zhang*, Yongchun Fang, Baoquan Li.  Visual Servoing Trajectory Tracking and Depth Identification for Mobile Robots with Velocity Saturation Constraints. IEEE Transactions on Industrial Electronics （T-IE）, 2023, accepted.

Abstract

         The paper proposes a novel visual servoing trajectory tracking controller satisfying velocity saturation constraints for mobile robots, which can simultaneously realize the unknown image depth identification. Compared with existing saturation controllers, the boundness of velocity commands can be explicitly determined though the control law is coupled with the unknown depth. In addition, the asymptotic stability (generally realizing UUB) is achieved theoretically in the presence of both velocity saturation constraints and the unknown depth parameter. To guarantee the velocity commands within the allowed speed limit, the saturation function is introduced into the visual servo control law to reshape tracking errors. Furthermore, to deal with the unknown depth, an adaptive updating law is skillfully constructed, which can simultaneously identify it under the persistent excitation (PE) condition. Also, to explicitly demonstrate the saturation performance of the designed visual servo controller, the boundness of velocity commands is analyzed, following which parameter selection rules are provided. The asymptotic convergence of tracking errors is theoretically proved with Lyapunov techniques. Finally, comparative experimental results show the effectiveness and superior performance of the proposed method.