用视觉和视线追踪让背托外骨骼更智能地辅助搬运。
From Vision to Assistance: Gaze and Vision-Enabled Adaptive Control for a Back-Support Exoskeleton
- 通过第一视角视觉+视线追踪实时识别抓取动作
- 启用视觉后助力量更大且更早，用户体感更轻松
- 适合需要人机协作的工业搬运场景
背托外骨骼可减轻工业搬运中的脊柱负荷，但其效果依赖于及时且情境感知的辅助。现有方法多依赖肌电或惯性传感，或使用不直接参与控制的视觉系统。本文提出一种基于第一视角视觉与可穿戴视线追踪的自适应控制框架，集成基于YOLO的实时抓取检测、有限状态机的任务状态判断及可变阻抗控制器，根据姿势与物体状态动态调节扭矩输出。15名参与者在三种条件下完成弯腰负重搬运实验（无外骨骼、无视觉外骨骼、有视觉外骨骼），结果表明：启用视觉后，辅助更早更强，主观疲劳感显著降低，流畅度、信任度与舒适度提升；问卷调查也显示用户更偏好视觉触发模式。研究证实，第一视角视觉能有效提升背托外骨骼的响应性、人体工学性、安全性与接受度。
原文摘要 · Abstract (English)
Back-support exoskeletons have been proposed to mitigate spinal loading in industrial handling, yet their effectiveness critically depends on timely and context-aware assistance. Most existing approaches rely either on load-estimation techniques (e.g., EMG, IMU) or on vision systems that do not directly inform control. In this work, we present a vision-gated control framework for an active lumbar occupational exoskeleton that leverages egocentric vision with wearable gaze tracking. The proposed system integrates real-time grasp detection from a first-person YOLO-based perception system, a finite-state machine (FSM) for task progression, and a variable admittance controller to adapt torque delivery to both posture and object state. A user study with 15 participants performing stooping load lifting trials under three conditions (no exoskeleton, exoskeleton without vision, exoskeleton with vision) shows that vision-gated assistance significantly reduces perceived physical demand and improves fluency, trust, and comfort. Quantitative analysis reveals earlier and stronger assistance when vision is enabled, while questionnaire results confirm user preference for the vision-gated mode. These findings highlight the potential of egocentric vision to enhance the responsiveness, ergonomics, safety, and acceptance of back-support exoskeletons.
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