基于多目标约束的六足动物机器人人类机器人指挥组合的优化方法
Xiaolei Chen1, Bo You1,2, Zheng Dong2
1The Key Laboratory of Intelligent Technology for Cutting and Manufacturing Ministry of Education, Harbin University of Science and Technology, Harbin, China.
这项研究介绍了一个机器人智能框架,以帮助驾驶员在复杂的地形上控制六足动物机器人. 该系统增强了人机协调,提高了机器人的稳定性,减少了碰撞.
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
- 人工智能的人工智能
背景情况:
- 在复杂的环境中远程控制六足动物机器人对人类驾驶员造成了重大负担.
- 现有的控制方法可能缺乏适应动态条件和驾驶员疲劳的智能.
研究的目的:
- 开发一个机器人智能框架,通过生成最佳的人机器人命令组合来协助人类驾驶员.
- 提高远程机器人操作中人机协调的效率和安全性.
主要方法:
- 根据决策目标提出了一个映射过程框架,用于生成基于决策目标的人机器人命令.
- 量化的人机状态约束,包括几何运动约束和驾驶员疲劳.
- 使用这些约束,实时优化和过可行的命令集.
- 使用可穿戴设备实施了协作驾驶控制系统.
主要成果:
- 使用推命令系统的驾驶员显示机器人行走稳定性得到改善.
- 通过拟议的系统,观察到机器人碰撞率的显著降低.
- 该系统有效地提高了远程操作期间的人机协调.
结论:
- 拟议的机器人智能框架成功地协助人类驾驶员完成复杂的远程控制任务.
- 基于量化约束的实时指挥建议提高了操作安全和效率.
- 可穿戴设备的集成有助于有效的人机器人协作控制.
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