基于脑机接口与双激光雷达的移动车导航系统

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (707 KB) HTML ( ) 输出: BibTeX \| EndNote (RIS)
引用本文:
孟丽霞, 陶霖密, 孙富春, 刘华平, 褚涛. 基于脑机接口与双激光雷达的移动车导航系统[J]. 机器人, 2012, 34(4): 449-454,459.. MENG Lixia, TAO Linmi, SUN Fuchun, LIU Huaping, CHU Tao. Vehicle Navigation System Based on BCI and Dual Laser Radar. ROBOT, 2012, 34(4): 449-454,459..

摘要

针对脑机接口信噪比低、准确率差和延时长等问题，提出了基于机器智能辅助的室外移动机器人脑机接口导航方法．设计并实现了一个基于脑机接口与双激光雷达的移动车导航系统．该系统首先采用了基于双激光雷达的改进的角度势场法进行局部路径规划，然后结合脑机接口系统获取的导航意图，经过融合决策给出控制命令，驱动一辆经过机械系统改装的电动汽车．实验表明，该系统能根据环境障碍信息和脑机控制意图实现智能避障与人机协同导航，具有更高的准确性、容错性和鲁棒性．

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS

关键词 ：脑机接口, 激光雷达, 移动机器人, 导航

Abstract：

A machine intelligence assistant BCI (brain-computer interface) navigation method for an outdoor mobile robot is put forward in view of the problem of BCI's low signal-to-noise ratio, bad accuracy and long time delay. A vehicle navigation system based on BCI and dual laser radar is designed and implemented. Firstly, an improved angle potential field method based on dual laser radar is used for local path planning, then with navigation intention from BCI system, control commands are generated by fusion decision and used for driving a electric vehicle with modified mechanical system. Experiments show that the system can realize intelligent obstacle avoidance and human-machine collaborative navigation based on environmental obstacle information and brain-machine interface control intention, and it has higher accuracy, tolerance and robustness.

Key words： brain-computer interface (BCI) laser radar mobile robot navigation

收稿日期: 2011-11-29 录用日期: 2012-06-04

ZTFLH:

TP391.4

基金资助:

国家自然科学基金资助项目（90820304,61075027）；清华信息科学与技术国家实验室（筹）学科交叉基金资助项目（042003023）

通讯作者: 孟丽霞 E-mail: mlx08@mails.tsinghua.edu.cn

作者简介: 孟丽霞（1971-），女，博士生，讲师．研究领域：机器人导航，机器学习．
陶霖密（1962-），男，博士，副教授．研究领域：认知机器视觉．
孙富春（1964-），男，博士，教授．研究领域：智能控制与网络．

链接本文:

https://robot.sia.cn/CN/ 或 https://robot.sia.cn/CN/Y2012/V34/I4/449

[1] 张钹,王田苗,邓志东,等. 机器人发展战略研究报告:历程、技术、产业、标准与政策[M]. 北京:兵器工业出版社,2009. Zhang B, Wang T M, Deng Z D, et al. Report on robot development strategy study: History, technology, industry, standard and policy[M]. Beijing: Weapon Industry Press, 2009.
[2] 蔡自兴,贺汉根,陈虹.未知环境中移动机器人导航控制研究的若干问题[J]. 控制与决策,2002,17(4): 385-390. Cai Z X, He H G, Chen H. Some issues for mobile robots navigation under unknown environments[J]. Control and Decision, 2002, 17(4): 385-390.
[3] 刘辉,杜玉晓,彭杰,等.脑-机接口技术发展[J]. 电子科技,2011,24(5): 116-119. Liu H, Du Y X, Peng J, et al. A review of brain-computer interface development[J]. Electronic Science and Technology, 2011, 24(5): 116-119.
[4] Wessberg J, Stambaugh C R, Kralik J D, et al. Real-time prediction of hand trajectory by ensembles of cortical neurons in primates[J]. Nature, 2000, 408(6810): 361-365.
[5] Lebedev M A, Nicolelis M A L. Brain-machine interfaces: Past, present and future[J]. Trends in Neurosciences, 2006, 29(9): 536-546.
[6] Millan Jd R, Renkens F, Mourio J, et al. Noninvasive brain-actuated control of a mobile robot by human EEG[J]. IEEE Transactions on Biomedical Engineering, 2004, 51(6): 1026-1033.
[7] Barbosa A O G, Achanccaray D R, Meggiolaro M A. Activation of a mobile robot through a brain computer interface[C]//IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 2010: 4815-4821.
[8] Galan F, Nuttin M, Lew E, et al. A brain-actuated wheelchair: Asynchronous and non-invasive brain-computer interfaces for continuous control of robots[J]. Clinical Neurophysiology, 2008, 119(9): 2159-2169.
[9] Iturrate I, Antelis J M, Kuebler A, et al. A noninvasive brain-actuated wheelchair based on a P300 neurophysiological protocol and automated navigation[J]. IEEE Transactions on Robotics, 2009, 25(3): 614-627.
[10] Bell C J, Shenoy P, Chalodhorn R, et al. Control of a humanoid robot by a noninvasive brain-computer interface in humans[J]. Journal of Neural Engineering, 2008, 5(2): 214-220.
[11] 邓志东,李修全,郑宽浩,等. 一种基于SSVEP的仿人机器人异步脑机接口控制系统[J].机器人,2011,33(1): 129-135. Deng Z D, Li X Q, Zheng K H, et al. A humanoid robot control system with SSVEP-based asynchronous brain-commuter interface[J]. Robot, 2011, 33(1): 129-135. [12] 欧青立,何克忠.室外智能移动机器人的发展及其关键技术研究[J].机器人,2000,22(6): 519-526.Ou Q L, He K Z. Research on key techniques and development of outdoor intelligent autonomous mobile robot[J]. Robot, 2000, 22(6): 519-526.
[13] Meng L X, Sun F C, Liu H P, et al. A fusion navigation of double laser radar for intelligent vehicle[J]. Advanced Materials Research, 2012, 346(1): 711-718.