CBF-Based Constrained Optimization for Safe and Adaptive CPG Gait Planning in Rehabilitation Robots

Le résumé fourni par la source

To address gait safety optimization in human-robot interaction during rehabilitation training, this paper proposes a safety-aware adaptive gait planning method integrating Control Barrier Function (CBF) and Central Pattern Generator (CPG) for synchronized motion between wearers and lower-limb exoskeletons. Initially, a CPG network generates biologically rhythmic trajectories with inter-joint coordination, while real-time adjustments of gait frequency and amplitude parameters are implemented based on the wearer's active torque. To mitigate safety risks induced by parameter adaptation, a hybrid constrained optimization framework is developed: By combining admittance modeling for human-robot dynamic characterization, a CBF-based safety constraint controller dynamically bounds CPG output parameters, guaranteeing biomechanically safe gait trajectories. Numerical simulations demonstrate the effectiveness of the proposed control strategy.

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