Human sensory-musculoskeletal modeling and control of whole-body movements

TL;DR

This paper introduces a comprehensive human sensory-musculoskeletal model, SMS-Human, integrated with multimodal sensory inputs and a hierarchical deep reinforcement learning framework to simulate and analyze complex human movements.

Contribution

The work presents a novel integrated model combining detailed anatomy, multisensory inputs, and advanced control algorithms for realistic movement simulation.

Findings

Close resemblance between simulated and natural human movements

Revealed musculoskeletal dynamics not directly measurable

Demonstrated versatile movement tasks including locomotion and object manipulation

Abstract

Coordinated human movement depends on the integration of multisensory inputs, sensorimotor transformation, and motor execution, as well as sensory feedback resulting from body-environment interaction. Building dynamic models of the sensory-musculoskeletal system is essential for understanding movement control and investigating human behaviours. Here, we report a human sensory-musculoskeletal model, termed SMS-Human, that integrates precise anatomical representations of bones, joints, and muscle-tendon units with multimodal sensory inputs involving visual, vestibular, proprioceptive, and tactile components. A stage-wise hierarchical deep reinforcement learning framework was developed to address the inherent challenges of high-dimensional control in musculoskeletal systems with integrated multisensory information. Using this framework, we demonstrated the simulation of three representative movement tasks, including bipedal locomotion, vision-guided object manipulation, and human-machine interaction during bicycling. Our results showed a close resemblance between natural and simulated human motor behaviours. The simulation also revealed musculoskeletal dynamics that could not be directly measured. This work sheds deeper insights into the sensorimotor dynamics of human movements, facilitates quantitative understanding of human behaviours in interactive contexts, and informs the design of systems with embodied intelligence.