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Towards EEG-Based Brain-Controlled Modular Robots: Preliminary Framework by Interfacing OpenVIBE, Python and V-REP for Simulate Modular Robot Control

机译:朝基于EEG的脑控制模块化机器人:通过接口开放式,Python和V-rep进行模拟模块机器人控制的初步框架

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Mostly in natural disaster situations, for example an earthquake, we will face a situation where people get trapped and unable to be found as soon as possible due to the unpredictable terrain. Hence, robot is being seen as scouts that able to adapt and perceive, and usually snake type robot is able to move throughout rubble and small confines. Then, the idea of using modular self-reconfigurable (MSR) robots based on CEBOT in 1988 spark an interest to researchers to fit the search and rescue purpose. Besides that, the idea of controlling robots without manual control but by using "thinking" have fascinated researchers and lead to the development of interfaces between human and machines. In 1970, a Brain Computer Interface (BCI) system has been establish and the BCI system usually is based on the Electroencephalogram (EEG) which is the electrical potentials generated in which the information generated by user and independent of any muscular activities. The implementations of both technologies to each other will frontier for a new alternatives which improves self-reconfigurable modular robot in term of control strategy. As a preliminary framework, a simulation is needed to determine both systems capabilities, and it can be achieved by interfacing the robot simulator, OpenVIBE and Virtual Experimentation Platform (V-REP) with the Python programming language. This study presentation will focus on how to control the modular robot in V-REP environment by using Python language which can be used for interfacing with BCI system created in OpenVIBE software and the simulated robot configuration. Each joint handles of modular robot based on V-REP hierarchy being streamed by Python language. There are several methods for establishment of communication between OpenVIBE and other applications. The method purpose in this paper will utilizing Lab Streaming Layer (LSL) and Python script as mediator. The outcome that is expected to be obtained for this study will be the success of communication establish to control virtual modular robot based on data from OpenVIBE. The future work based on this study will involving the BCI system designed using OpenVIBE and implementation to real modular robot might be applied.
机译:大多是在自然灾害情况下,例如地震,我们将要面对的人被困,无法找到尽快由于无法预知路况的情况。因此,机器人被视为侦察兵即能适应和感知,且通常为蛇型机器人能够在整个瓦砾和小界限移动。然后,使用基于CEBOT模块化自重构(MSR),机器人在1988年火花的想法感兴趣的研究人员,以适应搜索和救援目的。除此之外,控制,无需人工控制机器人,但通过使用“思维”的理念,有着迷的研究人员,并导致人类和机器之间界面的开发。在1970年,脑计算机接口(BCI)系统已经建立和BCI系统通常是基于脑电图(EEG),它是产生的电势,其中由用户生成的信息和独立于任何肌肉活动。这两种技术相互意志边疆从而提高了控制策略的期限自重构模块化机器人新的替代的实现。作为初步框架,需要模拟,以确定两个系统的功能,并且它可以通过连接在机器人模拟器来实现,OpenVIBE和虚拟实验平台(V-REP)与Python编程语言。该研究报告将重点放在如何利用它可用于在OpenVIBE软件创建BCI系统和仿真机器人配置接口Python语言来控制V-REP环境的模块化机器人。基于V-REP层次感模块化机器人的各关节手柄流通过Python语言。有设立OpenVIBE和其他应用程序之间的通信的几种方法。本文的方法目的将利用实验室流层(LSL)和Python脚本作为调解人。 ,预计这项研究将得到的结果将是沟通成功建立了基于从OpenVIBE数据来控制虚拟模块化机器人。在此基础上研究未来的工作将涉及使用OpenVIBE和实施真正的模块化机器人可以被应用于设计系统BCI。

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