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Real-time self-localization of a mobile robot by vision and motion system

机译:视觉和运动系统对移动机器人进行实时自我定位

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In this study, an autonomous robot is designed to equip an omni-vision camera and an omni-moving platform to meet the requirement of FIRA and RoboCup robot soccer competitions. To make robots obtain its location on the field, we use white-line pattern match localization algorithm to achieve this goal. However, when the white-line information is not complete during the matching process, the observed data has a huge difference with the pre-build database. Then the localization result will cause errors. In this study, we first introduce encoder localization algorithm to get robot's moving direction and even trace its motion as an odometer. Then we integrate the white-line pattern match localization and encoder localization as the proposed algorithm. The results demonstrate that the inetgration localization outperforms than the localization with white-line pattern match localization or encoder localization only. We can obtain robot location within 40 ms and with an error less than 10 cm by the algorithm. Meanwhile, the integration localization algorithm is compared with other schemes to show its accuracy.
机译:在这项研究中,自主机器人被设计为配备全视摄像头和全移动平台,以满足FIRA和RoboCup机器人足球比赛的要求。为了使机器人获得其在野外的位置,我们使用白线模式匹配定位算法来实现这一目标。但是,如果在匹配过程中白线信息不完整,则观察到的数据与预构建数据库会有很大差异。然后,本地化结果将导致错误。在这项研究中,我们首先介绍编码器定位算法,以获取机器人的运动方向,甚至以里程表的形式跟踪其运动。然后,我们将白线模式匹配定位和编码器定位集成为所提出的算法。结果表明,与白线模式匹配定位或仅编码器定位相比,嵌入定位的性能要好于白线模式的定位。通过算法,我们可以在40毫秒内获得机器人位置,并且误差小于10 cm。同时,将集成定位算法与其他方案进行比较以显示其准确性。

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