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Disturbance observer (DOB) based controller performs well in estimating and compensating for perturbation when the external or internal unknown disturbance is slowly time varying. However, to some extent, robot manipulators usually work in complex environment with high-frequency disturbance. Thereby, to enhance tracking performance in a teleoperation system, only traditional DOB technique is insufficient. In this paper, for the purpose of constructing a feasible teleoperation scheme, we develop a novel controller that contains a variable gain scheme to deal with fast-time varying perturbation, whose gain is adjusted linearly according to human surface electromyographic signals collected from Myo wearable armband. In addition, for tracking the motion of operator's arm, we derive five-joint-angle data of a moving human arm through two groups of quaternions generated from the armbands. Besides, the radial basis function neural networks and the disturbance observer-based control (DOBC) approaches are fused together into the proposed controller to compensate the unknown dynamics uncertainties of the slave robot as well as environmental perturbation. Experiments and simulations are conducted to demonstrated the effectiveness of the proposed strategy. Keywords Disturbance observer • Motion capture • Radial basis function neural networks • Teleoperation • Variable gain control 1 Introduction Robot teleoperation is a kind of advanced technology in which human operator/operators remotely control the far-end robot manipulator through computer intermediary (Sheridan 1995), and it plays an important role in healthcare, industrial B Chenguang Yang

Article (Accepted Version) http://sro.sussex.ac.uk Huang, Darong, Li, Bin, Li, Yanan and Yang, Chenguang (2022) Cooperative manipulation of deformable objects by single-leader-dual-follower teleoperation. IEEE Transactions on Industrial Electronics. p. 1.

Bimanual robots have been studied for decades and regulation on internal force of the being held object by two manipulators becomes a research interest in recent years. In this paper, based on impedance model, a method to obtain the optimal target position for bimanual robots to hold an object is proposed. We introduce a cost function combining the errors of the force and the position and manage to minimize its value to gain the optimal coordinates for the robot end effectors (EE). To implement this method, two necessary algorithms are presented, which are the closed-loop inverse kinematics (CLIK) method to work out joint positions from desired EE pose and the generalized-momentum-based external force observer to measure the subjected force acting on the EE so as to properly compensate for the joint torques. To verify the effectiveness, practicality, and adaptivity of the proposed scheme, in the simulation, a bimanual robot system with three degrees of freedom (DOF) in every manipulator was constructed and employed to hold an object, where the results are satisfactory.

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