让平衡球形机器人实现安全智能共控，无需双手操作。
Enabling Shared-Control for A Riding Ballbot System
- 采用新型被动人工势场法动态调节运动，避免传统方法的震荡与过度减速。
- 20名使用者实验表明，共控显著降低碰撞率和认知负担，且不减慢行进速度。
- 适合残障人士及辅助移动设备研究者，为无人操控安全导航提供新思路。
本研究提出一种名为PURE的共享控制方法，用于自平衡骑乘式球形机器人的避障。该系统具备动态稳定性、全向运动能力及无手操作界面，集成传感器阵列与新型被动人工势场（PAPF）方法，实现直观导航，支持减速辅助与触觉/音频反馈，有效降低碰撞风险。相比传统人工势场法，可避免控制振荡与复杂场景下的非必要减速。通过包含20名手动轮椅使用者及健全个体的人机交互实验，评估了室内导航与障碍物规避性能。结果表明，共享控制显著减少碰撞次数与认知负荷，且不影响行进速度，实现了直观安全的操作。研究证实该系统在自平衡助行设备避障领域具有高度适用性，填补了该方向的研究空白。
原文摘要 · Abstract (English)
This study introduces a shared-control approach for collision avoidance in a self-balancing riding ballbot, called PURE, marked by its dynamic stability, omnidirectional movement, and hands-free interface. Integrated with a sensor array and a novel Passive Artificial Potential Field (PAPF) method, PURE provides intuitive navigation with deceleration assistance and haptic/audio feedback, effectively mitigating collision risks. This approach addresses the limitations of traditional APF methods, such as control oscillations and unnecessary speed reduction in challenging scenarios. A human-robot interaction experiment, with 20 manual wheelchair users and able-bodied individuals, was conducted to evaluate the performance of indoor navigation and obstacle avoidance with the proposed shared-control algorithm. Results indicated that shared-control significantly reduced collisions and cognitive load without affecting travel speed, offering intuitive and safe operation. These findings highlight the shared-control system's suitability for enhancing collision avoidance in self-balancing mobility devices, a relatively unexplored area in assistive mobility research.
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