Human-Robot-Robot-Cooperation Based Uncalibrated Visual Servoing Control for Mobile Robotic Manipulators without Joint-State Feedback

When disposing hazardous goods, mobile robots mayn't feed back the joint state of its equipped manipulator due to the damage of measuring devices. To avoid the disposition time delay caused by recalling the robot, an HRRC (human-robot-robot-cooperation) based uncalibrated visual servoing control system is presented for the mobile robotic manipulator without joint-state feedback. Firstly, the virtual exoskeleton (virtual model) for reflecting the joint state of the manipulator is set up through selecting the joint regions artificially with human-computer-interaction (HCI) input devices (such as mouse) on the monitoring picture captured by the camera from another mobile robot. Then, the virtual exoskeleton is combined with the multi-joint tracking algorithm, to steer joints of the manipulator and maintain the posture of the end-effector. In order to guide the virtual exoskeleton using artificial guidance points, the relationship between the terminal of the virtual exoskeleton and joint angles is mapped by GRNN (general regression neural network). In the peg-in-hole experiment, the end-effector completes the task under the artificial guidance, and the posture of the end-effector can be maintained within an error of ±1° using the proposed method. Comparatively, the end-effector can neither complete the task, nor maintain its posture using the conventional single joint control method. Results of the contrast experiment verify that the proposed control system can assist operators to intuitively use the manipulator to dispose targets without any feedback of the joint states, and to maintain the end-effector in a desired posture during the disposition.