ROSep 5, 2021

Shaping Individualized Impedance Landscapes for Gait Training via Reinforcement Learning

arXiv:2109.02109v211 citations
AI Analysis

This work addresses the need for personalized and adaptive control in rehabilitation robotics to improve therapeutic outcomes, though it is incremental as it builds on existing assist-as-needed paradigms with a novel learning approach.

The paper tackled the problem of manually tuned impedance parameters in assist-as-needed robot-assisted rehabilitation by proposing a reinforcement learning-based controller that autonomously reshapes force fields based on individual motor abilities, experimentally showing adaptability and promotion of short-term motor adaptations in gait training with able-bodied subjects.

Assist-as-needed (AAN) control aims at promoting therapeutic outcomes in robot-assisted rehabilitation by encouraging patients' active participation. Impedance control is used by most AAN controllers to create a compliant force field around a target motion to ensure tracking accuracy while allowing moderate kinematic errors. However, since the parameters governing the shape of the force field are often tuned manually or adapted online based on simplistic assumptions about subjects' learning abilities, the effectiveness of conventional AAN controllers may be limited. In this work, we propose a novel adaptive AAN controller that is capable of autonomously reshaping the force field in a phase-dependent manner according to each individual's motor abilities and task requirements. The proposed controller consists of a modified Policy Improvement with Path Integral algorithm, a model-free, sampling-based reinforcement learning method that learns a subject-specific impedance landscape in real-time, and a hierarchical policy parameter evaluation structure that embeds the AAN paradigm by specifying performance-driven learning goals. The adaptability of the proposed control strategy to subjects' motor responses and its ability to promote short-term motor adaptations are experimentally validated through treadmill training sessions with able-bodied subjects who learned altered gait patterns with the assistance of a powered ankle-foot orthosis.

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