开发一个基于AR-BCI和SLAM导航的类人机器人控制系统
Yao Wang1, Mingxing Zhang1, Meng Li2
1Department of Life Sciences, Tiangong University, Tianjin, 300387 China.
Cognitive neurodynamics
|November 18, 2024
概括
这项研究介绍了一种增强现实脑计算机接口 (BCI),用于控制人形机器人. 该系统使用稳态视觉唤起潜能 (SSVEP) 和同时定位和映射 (SLAM) 进行高效,准确的导航和控制.
科学领域:
- 机器人和神经科学 机器人和神经科学
- 人与计算机的交互
- 增强现实是一种增强现实.
背景情况:
- 现有的机器人控制大脑-计算机接口 (BCI) 系统在人机交互友好和效率方面面临挑战.
- 需要基于BCI的人形机器人的直观和有效的控制策略,特别是用于日常护理和通信中的应用.
研究的目的:
- 开发和评估一种新型的人形机器人控制系统,将基于增强现实 (AR) 的BCI与自主室内导航的同时定位和映射 (SLAM) 集成在一起.
- 通过自主导航功能来减少用户工作负载,提高BCI控制机器人的效率和用户友好性.
主要方法:
- 基于8个目标稳定状态视觉唤起潜力 (SSVEP) 的BCI使用微软HoloLens进行视觉刺激呈现.
- 过器银行正规相关性分析 (FBCCA) 是一种没有培训的方法,用于SSVEP检测.
- 为自主室内导航集成了一个基于SLAM的方案,减少了对用户命令连续传输的需求.
主要成果:
- 开发的BCI系统在选择八个命令中的一个时,平均准确率达到了94.79%.
- 自主导航子系统成功引导人形机器人到用户指定的目的地.
- 所有12名健康参与者在没有事先培训的情况下都有效地完成了实验任务,证明了系统的可行性.
结论:
- 集成的AR-BCI和SLAM系统为控制人形机器人提供了一种可行和高效的方法.
- 这种新型系统显示了改进基于BCI的机器人控制策略的巨大潜力,特别是在辅助技术和人机交互方面.
- 开发的系统表现出高精度和用户友好性,为机器人和神经技术的先进应用铺平了道路.
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