空気圧駆動ソフト外骨格スーツのためのタスク非依存な動的支援制御戦略
A Task-Agnostic Control Strategy for Dynamic Assistance with Pneumatically Actuated Soft Exosuits
空気圧アクチュエータの複雑なダイナミクスをハンマーシュタイン動的モデルで表現し、その逆モデルを制御ループに組み込むことで、ユーザーの意図推定に生理・力センサを必要とせず、タスク非依存で動的な支援を実現する制御戦略を提案した。手首用ソフト外骨格のテストリグで評価し、支援なしと比べて相互作用トルクを最大73%、主要筋の活性を最大47%削減した。
著者: Anoush Sepehri, Zachary Huang, Raymond de Callafon, Michael T. Tolley, Tania K. Morimoto
分類: cs.RO, cs.HC
原文アブストラクト
Pneumatic artificial muscles have provided new opportunities to develop upper-extremity soft exosuits for reha- bilitation, augmentation, and assisted daily living. However, the complex dynamics and limited bandwidth of these actuators has made providing responsive assistance based on user intention a longstanding challenge. In this work, we present an inverse-plant control strategy for pneumatically actuated soft exosuits that only relies on kinematic sensing for task-agnostic and dynamic assistance during daily living. We model the human-robot system using a Hammerstein dynamic model, consisting of a Preisach hysteresis model and a linear time-invariant filter, to capture the static and dynamic behavior of the system. We personalize our model to each user using 140 s of data and approximate an inverse to integrate into our control loop. When evaluated on a test rig that emulated a soft assistive exosuit for the wrist, our controller reduced the interaction torque by up to 73% and the activation of key flexor and extensor muscles by up to 47% relative to the condition with no assistance for speeds ranging from 8°/s to 120°/s. Overall, this work presents a control strategy that can provide task-agnostic, dynamic assistance with pneumatically actuated soft exosuits without the need for physiological or force sensors to interpret user intention.