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Development of Autonomous Mobile Robot 'MML-05' Based on i-Cart Mini for Tsukuba Challenge 2015

机译:2015年筑波挑战赛基于i-Cart Mini的自主移动机器人“ MML-05”的开发

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This paper describes a self-localization method for autonomous mobile robots entered in the Tsukuba Challenge 2015. One of the important issues in autonomous mobile robots is accurately estimating self-localization. An occupancy grid map, created manually before self-localization has typically been utilized to estimate the self-localization of autonomous mobile robots. However, it is difficult to create an accurate map of complex courses. We created an occupancy grid map combining local grid maps built using a leaser range finder (LRF) and wheel odometry. In addition, the self-localization of a mobile robot was calculated by integrating self-localization estimated by a map and matching it to wheel odometry information. The experimental results in the final run of the Tsukuba Challenge 2015 showed that the mobile robot traveled autonomously until the 600 m point of the course, where the occupancy grid map ended.
机译:本文介绍了进入2015年筑波挑战赛的自主移动机器人的自定位方法。自主移动机器人的重要问题之一是准确估计自定位。通常在利用自定位之前手动创建的占用栅格图来估计自主移动机器人的自定位。但是,很难创建准确的复杂课程图。我们结合了使用租车者测距仪(LRF)和车轮里程表构建的本地栅格地图,创建了一个占用栅格地图。另外,通过整合由地图估算的自定位并将其与车轮里程计信息进行匹配,可以计算出移动机器人的自定位。在2015年筑波挑战赛的最后阶段的实验结果表明,移动机器人自主行驶直到路线600 m处,占用网格图结束。

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