Enhancing the Autonomy of Teleoperated Redundant Manipulators Through Fusion of Intelligent Control Modules

Abstract

This paper presents a method for redundancy resolution of an industrial manipulator in a teleoperated force control task. A seven degree-of-freedom (DOF) industrial manipulator manufactured by the Mitsubishi Heavy Industries Ltd. is used for experiments. The task involves obeying a force command sent from a remote computer while autonomously adapting the posture to avoid unexpected obstacles moving toward the manipulator. Redundancy resolution is employed for autonomous adaptation of the configuration to avoid the obstacle while continuing the force control task. This self-adaptive skill on the slave manipulator side is very important because teleoperation is often performed in dangerous or partially unknown environments where unexpected changes such as moving obstacles can well be expected. In such situations, the control ability of the master side is very limited due to the practical limitations of vision sensors to capture a comprehensive view of the environment and the limitations of the degrees of freedom on the master manipulator. The proposed method relies on two modules of an intelligent controller on the slave side. The first is an on-line fuzzy neural network (FNN) for intelligent force control, and the second is a configuration controller that works in harmony with the first to exploit redundancy to react to avoid moving obstacles such that the latter does not inhibit the progress of the former. The second controller generates joint velocity commands in null space of the hand Jacobian, so that its activation does not affect the force controller. Here we show that the proposed method can skillfully avoid a moving obstacle without stopping the force control task. This skillful adaptation ability can significantly improve the efficiency and safety of teleoperated force control tasks with less burden on the master side. This paper presents some promising experimental results to demonstrate the effectiveness of the proposed method.