Development of a Testbed for Robotic Neuromuscular Controllers

Abstract

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.