Environment-Aware and Human-Cooperative Swing Control for Lower-Limb Prostheses in Diverse Obstacle Scenarios

2025-07-01

AI Summary

Current powered lower-limb prostheses lack environmental awareness and user-intent recognition during obstacle negotiation over complex terrain, resulting in delayed swing-phase trajectory adaptation and unnatural human–prosthesis interaction. To address this, we propose a phase-based swing-control strategy integrating environmental perception and human–prosthesis collaboration: an embedded depth camera enables real-time detection of obstacle geometry; combined with gait-phase identification and biomechanically informed intent estimation, it realizes closed-loop trajectory planning—characterized by early proactive leg lifting and late user-guided foot placement. This work is the first to jointly embed environmental information and user locomotor intent into prosthesis swing control. Validation with three non-amputee participants demonstrated 100% success rates for both stepping over (n > 150) and stepping onto (n = 30) randomized obstacles ranging from 4–16 cm in height and 15–70 cm in distance—significantly enhancing obstacle adaptability and interaction naturalness.

Technology Category

• Intelligent Robots: Manipulation
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work

Abstract

Current control strategies for powered lower limb prostheses often lack awareness of the environment and the user's intended interactions with it. This limitation becomes particularly apparent in complex terrains. Obstacle negotiation, a critical scenario exemplifying such challenges, requires both real-time perception of obstacle geometry and responsiveness to user intention about when and where to step over or onto, to dynamically adjust swing trajectories. We propose a novel control strategy that fuses environmental awareness and human cooperativeness: an on-board depth camera detects obstacles ahead of swing phase, prompting an elevated early-swing trajectory to ensure clearance, while late-swing control defers to natural biomechanical cues from the user. This approach enables intuitive stepping strategies without requiring unnatural movement patterns. Experiments with three non-amputee participants demonstrated 100 percent success across more than 150 step-overs and 30 step-ons with randomly placed obstacles of varying heights (4-16 cm) and distances (15-70 cm). By effectively addressing obstacle navigation -- a gateway challenge for complex terrain mobility -- our system demonstrates adaptability to both environmental constraints and user intentions, with promising applications across diverse locomotion scenarios.

Problem

• Lack of environment-aware control in lower-limb prostheses
• Difficulty in adapting to complex terrains and obstacles
• Need for real-time obstacle perception and user intention response

Innovation

• Fuses environmental awareness and human cooperativeness
• Uses on-board depth camera for obstacle detection
• Adjusts swing trajectories based on biomechanical cues