Development of a Testbed for Robotic Neuromuscular Controllers

Current control approaches to robotic legged locomotion rely on centralized planning and tracking or motion pattern matching. Central control is not available to robotic assistive devices that integrate with humans, and matching predefined patterns severely limits user dexterity. By contrast, biological systems show substantial legged dexterity even when their central nervous system is severed from their spinal cord, indicating that neuromuscular feedback controls can be harnessed to encode stability, adaptability, and maneuverability into legged systems. Here we present the initial steps to develop a robotic gait testbed that can implement and verify neuromuscular controls for robotic assistive devices. The initial stage consists of an antagonistically actuated two segment leg with a floating compliant joint. We detail its electromechanical design and low level, velocity-based torque control. Additionally, we present experiments that test the leg's performance during human-like high fidelity motions. The results show that the robot can track fast motions corresponding to 87% of the maximum performance limit of human muscle. The experiments also reveal limitations of our current implementation and we discuss solutions to overcoming them.