Brainless Running: A Quasi-quadruped Robot with Decentralized Spinal Reflexes by Solely Mechanical Devices

As a strategy to address the difficulties encountered when modeling and controlling a musculoskeletal system, we present a straightforward implementation of an autonomous decentralized motion control system in this paper; the system is inspired by the spinal reflex system of animals. We developed an artificial receptor, a muscle, and a neuron to mechanically implement the reflex mechanisms of animals. Among the reflex mechanisms, this paper presents a reflex system with reciprocal innervation for a musculoskeletal quasi-quadruped robot, including antagonist muscles. In the experiments, the robot autonomously generated a leg trajectory and a gait pattern with smooth alternating motions of the antagonist muscles through the interaction between the body, the ground, and the artificial reflex systems. To evaluate the reciprocal innervation, we compared the developed robot with one that does not include antagonist muscles. The reciprocal innervation allows for twice as many muscle implementations as those offered by the robot without antagonist muscles. Moreover, it improves the running speed by 5% on average and the flexion and extension velocities of all joints by 28% on average at around touchdowns and liftoffs of the foot. This successful result lead to implement more advanced nervous systems by solely mechanical devices.