Nguyen Jordan S, Nguyen Tuan Nghia, Tran Yvonne, Su Steven W, Craig Ashley, Nguyen Hung T
Faculty of Engineering and Information Technology, University of Technology, Sydney, Broadway, NSW 2007, Australia.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:3069-72. doi: 10.1109/EMBC.2012.6346612.
This paper is concerned with the operational performance of a semi-autonomous wheelchair system named TIM (Thought-controlled Intelligent Machine), which uses cameras in a system configuration modeled on the vision system of a horse. This new camera configuration utilizes stereoscopic vision for 3-Dimensional (3D) depth perception and mapping ahead of the wheelchair, combined with a spherical camera system for 360-degrees of monocular vision. The unique combination allows for static components of an unknown environment to be mapped and any surrounding dynamic obstacles to be detected, during real-time autonomous navigation, minimizing blind-spots and preventing accidental collisions with people or obstacles. Combining this vision system with a shared control strategy provides intelligent assistive guidance during wheelchair navigation, and can accompany any hands-free wheelchair control technology for people with severe physical disability. Testing of this system in crowded dynamic environments has displayed the feasibility and real-time performance of this system when assisting hands-free control technologies, in this case being a proof-of-concept brain-computer interface (BCI).
本文关注的是一种名为TIM(思维控制智能机器)的半自动轮椅系统的运行性能,该系统在以马的视觉系统为模型的系统配置中使用摄像头。这种新的摄像头配置利用立体视觉进行三维(3D)深度感知和轮椅前方的映射,同时结合球形摄像头系统实现360度单目视觉。这种独特的组合使得在实时自主导航过程中,能够对未知环境的静态组件进行映射,并检测任何周围的动态障碍物,最大限度地减少盲点,防止与人员或障碍物发生意外碰撞。将这种视觉系统与共享控制策略相结合,可在轮椅导航过程中提供智能辅助引导,并可与任何用于严重身体残疾人士的免提轮椅控制技术配合使用。在拥挤的动态环境中对该系统进行测试,展示了该系统在辅助免提控制技术时的可行性和实时性能,在这种情况下是一种概念验证脑机接口(BCI)。