Human-Exoskeleton Disagreement Resolution Through Interaction Torque Minimization: Experimental Results

This paper presents experimental validation of a recently proposed Assist-As-Needed controller which utilizes human-robot interaction force to adapt the exoskeleton's reference trajectory. Using the estimated dynamics of Indego lower-limb exoskeleton in single and double support regimes, we accurately estimate the human-exoskeleton interaction torques all over the gait cycle. This enables the exoskeleton to adapt its desired joint angle trajectories by minimizing its physical interaction with the user, thereby resolving the human-exoskeleton physical disagreement. The results of our experiments on two able-bodied participants show that the proposed reference trajectory adaptation method can boost performance metrics such as assistance efficiency and assistance coordination with user intention. Moreover, we observed reductions in muscular activity, with decreases ranging from 13% to 54%, across muscles acting on the hip or knee joints. While direct measures of gait stability were not assessed, the proposed trajectory adaptation is associated with improved foot clearance metrics, specifically minimum toe and maximum heel clearance. This improvement, coupled with a reduction in users' muscle activity, may suggest enhancements in perceived stability compared to using a fixed desired trajectory for controlling the exoskeleton.