Development of a humanoid robot control system based on AR-BCI and SLAM navigation

IF 3.1 3区 工程技术 Q2 NEUROSCIENCES
Yao Wang, Mingxing Zhang, Meng Li, Hongyan Cui, Xiaogang Chen
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Abstract

Brain-computer interface (BCI)-based robot combines BCI and robotics technology to realize the brain’s intention to control the robot, which not only opens up a new way for the daily care of the disabled individuals, but also provides a new way of communication for normal people. However, the existing systems still have shortcomings in many aspects such as friendliness of human–computer interaction, and interaction efficient. This study developed a humanoid robot control system by integrating an augmented reality (AR)-based BCI with a simultaneous localization and mapping (SLAM)-based scheme for autonomous indoor navigation. An 8-target steady-state visual evoked potential (SSVEP)-based BCI was implemented to enable direct control of the humanoid robot by the user. A Microsoft HoloLens was utilized to display visual stimuli for eliciting SSVEPs. Filter bank canonical correlation analysis (FBCCA), a training-free method, was used to detect SSVEPs in this study. By leveraging SLAM technology, the proposed system alleviates the need for frequent control commands transmission from the user, thereby effectively reducing their workload. Online results from 12 healthy subjects showed this developed BCI system was able to select a command out of eight potential targets with an average accuracy of 94.79%. The autonomous navigation subsystem enabled the humanoid robot to autonomously navigate to a destination chosen utilizing the proposed BCI. Furthermore, all participants successfully completed the experimental task using the developed system without any prior training. These findings illustrate the feasibility of the developed system and its potential to contribute novel insights into humanoid robots control strategies.

Abstract Image

开发基于 AR-BCI 和 SLAM 导航的仿人机器人控制系统
基于脑机接口(BCI)的机器人将BCI与机器人技术相结合,实现了大脑对机器人的意向控制,不仅为残疾人的日常护理开辟了一条新途径,也为正常人提供了一种新的交流方式。然而,现有系统在人机交互的友好性、交互效率等诸多方面仍存在不足。本研究通过将基于增强现实(AR)的生物识别(BCI)与基于同步定位和映射(SLAM)的室内自主导航方案相结合,开发了一种仿人机器人控制系统。该系统实施了基于8目标稳态视觉诱发电位(SSVEP)的BCI,使用户能够直接控制仿人机器人。微软HoloLens用于显示视觉刺激,以诱发SSVEP。滤波器组典型相关分析(FBCCA)是一种无需训练的方法,在本研究中用于检测 SSVEPs。通过利用 SLAM 技术,拟议的系统减轻了用户频繁发送控制指令的需要,从而有效减轻了用户的工作量。12 名健康受试者的在线结果显示,所开发的 BCI 系统能够从 8 个潜在目标中选择一个指令,平均准确率为 94.79%。自主导航子系统使仿人机器人能够自主导航到利用所提出的生物识别(BCI)技术选择的目的地。此外,所有参与者都使用开发的系统成功完成了实验任务,而无需事先接受任何培训。这些研究结果表明了所开发系统的可行性及其为仿人机器人控制策略提供新见解的潜力。
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来源期刊
Cognitive Neurodynamics
Cognitive Neurodynamics 医学-神经科学
CiteScore
6.90
自引率
18.90%
发文量
140
审稿时长
12 months
期刊介绍: Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models. The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome. The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged. 1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics. 2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages. 3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.
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