Control strategies for the index finger of a tendon-driven hand

To understand how versatile dexterity is achieved in the human hand and to achieve it in a robotic form, we have constructed an anatomically correct testbed (ACT) hand. This paper focuses on the development of control strategies for the index finger motion and implementation of joint passive behavior in the ACT hand. A direct muscle position control and a force-optimized joint control are implemented for position tracking through muscle force control. The relationships between the muscle and joint motions play a critical role in both of the controllers and we implemented a Gaussian process regression technique to determine these relationships. Our experiments demonstrate that the direct muscle position controller allows for fast position tracking, while the force-optimized joint controller allows for the exploitation of actuation redundancy in the finger critical for this redundant system. We demonstrate that by implementing a passive force-length relationship at each muscle we are able to precisely match joint stiffness of the metacarpophalangeal (MCP) joint of the ACT to that of a human MCP joint. We also show the results from improved position tracking when implemented in the presence of passive muscle control schemes. The control schemes for position tracking and passive behavior are inspired by human neuromuscular control, and form the building blocks for developing future human-like control approaches.