Bipedal Balance Control with Whole-body Musculoskeletal Standing and Falling Simulations
This work addresses balance impairments in humans and humanoid robotics by providing muscle-level insights, though it is incremental in applying existing simulation methods to this specific domain.
The authors tackled the problem of static balance and falling in bipedal systems by developing a hierarchical control pipeline for whole-body musculoskeletal simulations, resulting in insights into stable standing, muscle injury effects, and fall patterns aligned with clinical data, with simulated hip exoskeleton assistance improving balance maintenance and reducing muscle effort under perturbation.
Balance control is important for human and bipedal robotic systems. While dynamic balance during locomotion has received considerable attention, quantitative understanding of static balance and falling remains limited. This work presents a hierarchical control pipeline for simulating human balance via a comprehensive whole-body musculoskeletal system. We identified spatiotemporal dynamics of balancing during stable standing, revealed the impact of muscle injury on balancing behavior, and generated fall contact patterns that aligned with clinical data. Furthermore, our simulated hip exoskeleton assistance demonstrated improvement in balance maintenance and reduced muscle effort under perturbation. This work offers unique muscle-level insights into human balance dynamics that are challenging to capture experimentally. It could provide a foundation for developing targeted interventions for individuals with balance impairments and support the advancement of humanoid robotic systems.