Variable Impedance Control for Floating-Base Supernumerary Robotic Leg in Walking Assistance
Jun Huo, Kehan Xu, Chengyao Li, Yu Cao, Jie Zuo, Xinxing Chen, Jian Huang
TL;DR
This work tackles safety and adaptability in force control for a loosely coupled floating-base supernumerary robotic leg (SRL) during walking. It blends a model-based loosely coupled dynamics formulation with a hybrid position/force control scheme and a state-dependent variable impedance control (VIC) strategy. A real-time impedance-parameter generator network (RSG-IPGN) guarantees stability while dynamically switching impedance across gait phases, enabling softer ground contact and stronger support when needed. Simulations and treadmill experiments with healthy participants demonstrate that VIC improves safety and interaction quality, offering a practical path toward personalized, gait-variant walking assistance for hemiplegia and rehabilitation scenarios.
Abstract
In human-robot systems, ensuring safety during force control in the presence of both internal and external disturbances is crucial. As a typical loosely coupled floating-base robot system, the supernumerary robotic leg (SRL) system is particularly susceptible to strong internal disturbances. To address the challenge posed by floating base, we investigated the dynamics model of the loosely coupled SRL and designed a hybrid position/force impedance controller to fit dynamic torque input. An efficient variable impedance control (VIC) method is developed to enhance human-robot interaction, particularly in scenarios involving external force disturbances. By dynamically adjusting impedance parameters, VIC improves the dynamic switching between rigidity and flexibility, so that it can adapt to unknown environmental disturbances in different states. An efficient real-time stability guaranteed impedance parameters generating network is specifically designed for the proposed SRL, to achieve shock mitigation and high rigidity supporting. Simulations and experiments validate the system's effectiveness, demonstrating its ability to maintain smooth signal transitions in flexible states while providing strong support forces in rigid states. This approach provides a practical solution for accommodating individual gait variations in interaction, and significantly advances the safety and adaptability of human-robot systems.
