A neuromuscular locomotion controller that realizes human-like responses to unexpected disturbances

In this paper, we demonstrate that a neuromuscular controller built based on the human anatomical structure and motion data can realize human-like responses to unexpected disturbances during locomotion. This particular work concerns the response to trips due to obstacles and shows that the two strategies identified in biomechanics emerge from a single controller. We first identify the parameters of a neuromuscular network model using the muscle tension data during a human walking motion. The anatomically-correct network models the somatosensory reflex of the human neuromuscular system. We use this network as the controller for a musculoskeletal human model to simulate its response to disturbances. Simulation results show that our neuromuscular controller automatically results in the appropriate trip recovery strategy with a single set of parameters, although we do not explicitly model the trip response or the condition to invoke each strategy. This result implies that an appropriately designed locomotion controller can also provide rapid responses to trips without deliberate controller selection or planning.