基于云的运动分析和导航用于可穿戴机器人应用程序的概念化
David Schick1, Johannes Schick1, Jonas Paul David1
1Institute for High Integrity Mechatronics Systems, Aalen University, 73430 Aalen, Germany.
Sensors (Basel, Switzerland)
|August 10, 2024
概括
预测可穿戴机器人的行人行为是一项挑战. 这项研究介绍了一个使用地理映射和人类活动识别 (HAR) 的云系统,为外骨和活跃的形提供背景.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人与计算机的交互
- 计算机科学 计算机科学
背景情况:
- 在不受限制的环境中,行人行为是不可预测的.
- 可穿戴机器人,包括下肢外骨和活跃形,需要适应性支持,以进行各种步行活动,如平行步行和爬楼梯.
- 预测和支持不同步态活动之间的过渡是当前可穿戴机器人系统面临的重大挑战.
研究的目的:
- 为可穿戴机器人提出一个新的云软件系统.
- 通过提供行人行为上下文意识来增强下肢外骨和活跃骨架的适应能力.
- 为了应对在不受约束的环境中不可预测的步态过渡的挑战.
主要方法:
- 开发一个集成地理绘图技术的云软件系统.
- 实施人类活动识别 (HAR) 算法来解释行人行为.
- 在现实世界中部分实施和测试拟议的系统.
主要成果:
- 开发的系统提供了事后信息,为周围的行人提供了背景信息.
- 最初的测试表明该系统的概念是可行的.
- 该系统显示了未来发展的显著可扩展性前景.
结论:
- 拟议的基于云的系统提供了一个有希望的方法来增强可穿戴机器人的功能.
- 整合地理映射和HAR可以提高下肢外骨和活跃骨架的适应性.
- 该系统提供上下文信息的能力显示了在动态环境中更安全,更直观的人机交互的潜力.
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