Muscle force distribution for adaptive control of a humanoid robot arm with redundant bi-articular and mono-articular muscle mechanism

  • Authors:
  • Haiwei Dong;Nikolaos Mavridis

  • Affiliations:
  • New York University AD, Abu Dhabi, UAE;New York University AD, Abu Dhabi, UAE

  • Venue:
  • Artificial Life and Robotics
  • Year:
  • 2013

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Abstract

Robot arms driven by bi-articular and mono-articular muscles have numerous advantages. If one muscle is broken, the functionality of the arm is not influenced. In addition, each joint torque is distributed to numerous muscles, and thus the load of each muscle can be relatively small. This paper addresses the problem of muscle control for this kind of robot arm. A relatively mature control method (i.e. sliding mode control) was chosen to get joint torque first and then the joint torque was distributed to muscle forces. The muscle force was computed based on a Jacobian matrix between joint torque space and muscle force space. In addition, internal forces were used to optimize the computed muscle forces in the following manner: not only to make sure that each muscle force is in its force boundary, but also to make the muscles work in the middle of their working range, which is considered best in terms of fatigue. Besides, all the dynamic parameters were updated in real-time. Compared with previous work, a novel method was proposed to use prediction error to accelerate the convergence speed of parameter. We empirically evaluated our method for the case of bending-stretching movements. The results clearly illustrate the effectiveness of our method towards achieving the desired kinetic as well as load distribution characteristics.