Adaptive Vision-Based Control for Rope-Climbing Robot Manipulator

While the mechanism of Rope-Climbing provides much flexibility, it opens up challenges to the development of the controller for Robotic Manipulator installed on Rope-Climbing robot(RCR), which is called Rope-Climbing Robot Manipulator(RCRM) here. In particular, the deformable nature of the rope results in the vibration to the manipulator and hence affects the positioning of the end effector. In this paper, a new adaptive vision-based controller is proposed for RCRM, which enables the robot to carry out the high-accuracy task under the unknown vibration from the rope. The proposed controller guarantees the performance of the robot in twofold. First, the control problem is directly formulated in the image space such that the exact spatial relationship between the moving base of the manipulator (due to the vibrating rope) and the target (e.g. the wall) is not required. Second, novel adaptation laws are developed to estimate the vibration from the rope online and are cancelled out in the robot control input to stabilize the end effector. The stability of the closed-loop system is rigorously proved with Lyapunov methods, and experimental results are presented to illustrate the performance of the proposed controller.