智能机器人的多式融合和人机交互控制智能机器人的控制
Tao Gong1, Dan Chen1, Guangping Wang2
1Institute of Intelligent Manufacturing, Shenzhen Polytechnic University, Shenzhen, China.
Frontiers in bioengineering and biotechnology
|January 19, 2024
概括
本研究介绍了用于步行康复的康复机器人步行者 (RRW),提供行走辅助和体重支持 (BWS). 新系统准确地识别用户的意图,以提高恢复期间的移动性和安全性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 康复工程 康复工程 康复工程
- 人与计算机的交互
背景情况:
- 由于患者人数的增加和当前设备的局限性,对先进的康复解决方案的需求日益增加.
- 小规模的机器人步行者对于日常生活活动 (ADL) 的帮助至关重要.
- 现有的步行康复方法在提供一致的支持和模仿治疗师运动方面面临挑战.
研究的目的:
- 提出和评估一款用于步行康复的新型康复机器人步行者 (RRW).
- 在康复期间提供行走辅助和体重支 (BWS).
- 开发一个准确的人类意图识别系统,以实现无的人机交互.
主要方法:
- 开发一个带有全向移动平台,BWS机制和骨盆支架的RRW系统.
- 整合力传感器,操纵杆和深度传感摄像头,用于人机数据采集.
- 通过机器人动力学实现多式融合算法,用于通过机器人动力学识别意图和运动控制.
主要成果:
- 与三名志愿者进行的初步测试证明了该系统的运动控制能力.
- 拟议的多式融合算法实现了平均整方位误差 (ISE) 2.90.
- 该系统成功提供了步行辅助,验证了拟议方法的效率.
结论:
- 开发的RRW系统在提供步行康复援助方面是有效的.
- 多模式融合算法提高了人类意图识别的准确性.
- 该RRW为接受康复的患者提供安全,自然和舒适的环境.
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