The coordination problem of a human arm and a robot manipulator is explored using compliant motion and predictive control. The problem arises when a human arm and a robot manipulator coordinate for the execution of a task in unscheduled task environment. In such scenarios the arm, by virtue of its intelligence, is assumed to lead the task while the manipulator is required to comply with the motion of the arm and support the object load. Such a scheme is superior to the better known multiple manipulator coordination problem, which normally assumes known trajectories and a structured task environment. By coordinating manipulator with the arm of its operator the uncertainty due to the environment can be reduced while load sharing can help relieve the arm of the physical strain. This paper addresses the problem in the framework of model-based predictive control. The transfer function from the manipulator position command to the wrist sensor force output is defined. The desired set point for the manipulator force is set to equal the gravitational force. A predictive control scheme is then used to design a two-degree of freedom controller for the problem. The simulation results indicate that the manipulator effectively takes over the object load and the arm force stays close to zero. Moreover, the manipulator is seen to be highly responsive to the arm movement and relatively small arm force can effectively initiate the manipulation task.
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