一个移动机器人的持续共享控制,具有脑-计算机接口和自主导航,用于日常协助
Baoguo Xu1, Deping Liu1, Muhui Xue1
1State Key Laboratory of Bioelectronics, Jiangsu Key Laboratory of Remote Measurement and Control, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Computational and structural biotechnology journal
|August 21, 2023
概括
本研究介绍了脑与计算机接口 (BCI) 和移动机器人的持续共享控制策略. 该系统可为辅助设备提供有效的导航,增强用户控制和任务完成.
科学领域:
- 神经科学是一个神经科学.
- 机器人技术 机器人技术 机器人技术
- 人与计算机的交互
背景情况:
- 基于脑电图 (EEG) 的脑电脑接口 (BCI) 显示出对康复和援助的希望.
- 实现对大脑驱动的移动机器人持续控制仍然是一个重大挑战.
研究的目的:
- 建议和验证移动机器人系统的持续共享控制战略.
- 整合连续的BCI控制与自主导航,以增强机器人操作.
- 根据用户的性能,动态调整BCI输入和自主导航之间的平衡.
主要方法:
- 开发了一种连续的共享控制策略,将连续的BCI和自主导航相结合.
- 利用基于视觉的同时定位和映射 (SLAM) 进行环境映射.
- 实施基于大脑的共享控制动态窗口方法 (BSC-DWA) 进行轨迹评估.
- 进行了两阶段的培训和在线共享控制实验与人类受试者.
主要成果:
- 素朴的受试者在持续控制过程中取得了很高的成绩,平均百分比有效正确率约为97%,总正确率在训练过程中超过80%.
- 所有参与者都在未知的走廊中使用连续共享控制系统成功完成了导航任务.
- 该系统在整合连续BCI,共享控制,自主导航和视觉SLAM方面展示了可行性和有效性.
结论:
- 拟议的持续共享控制框架对于BCI驱动的移动机器人导航是可行的和有效的.
- 这种方法显示出大脑驱动的辅助移动机器人和轮椅在日常应用中的巨大潜力.
- BCI和自主导航的动态融合增强了复杂任务的控制能力.
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