可转换的四轮式轮椅:通过模式调节的政策蒸实现统一的行走和轮式机动
Atsuki Akamisaka1, Katashi Nagao1
1Department of Intelligent Systems, Graduate School of Informatics, Nagoya University, Nagoya 464-8603, Japan.
Sensors (Basel, Switzerland)
|January 28, 2026
概括
这项研究介绍了一种可转换的四足轮椅,它使用强化学习来适应地形导航. 通过切换行走和轮式模式,它显著提高了轮椅用户的移动效率.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 生物力学 生物力学
背景情况:
- 轮椅使用者由于楼梯和不均的表面等物理障碍而面临着移动限制.
- 现有的无障碍设计在完全消除这些障碍方面存在局限性.
研究的目的:
- 为了验证可转换的四足轮椅的有效性,能够在行走和车轮模式之间切换.
- 提高轮椅乘客在不同环境中的移动效率.
主要方法:
- 利用近距离政策优化 (PPO) 进行强化学习,以开发步行和轮式旅行策略.
- 采用NVIDIA Isaac Sim进行现实的机器人模拟.
- 对乘客加速数据进行频率分析,以评估两种模式的稳定性.
主要成果:
- 步行模式表现出周期性垂直振动约2赫兹.
- 车轮模式表现出极小的振动,表明运行稳定.
- 与单模式运行相比,适应性切换模式显著提高了移动效率.
结论:
- 可转换的四足轮椅通过适应不同地形,有效地提高了流动性.
- 学习多种专业策略并在它们之间切换是有效的机器人穿越的可行方法.
- 这项技术为克服轮椅使用者所面临的物理障碍提供了一个有希望的解决方案.
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