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Development of the Autonomous Mobile Robot for Target-Searching in Urban Areas in the Tsukuba Challenge 2013

机译:2013年筑波挑战赛中用于城市目标搜索的自主移动机器人的开发

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This paper describes a navigation method for autonomous mobile robots and the knowledge obtained through trial runs conducted during the Tsukuba Challenge 2013 whose main tasks were autonomous navigation by robots to a goal and searching for target persons in several urban areas. Accurate maps are an important tool in localization on complex courses. We constructed occupancy grid map making method using laser scanners, gyro-assisted odometry and a DGPS. In trial runs, robots detect target parsons two ways - one involving color detection in images and the other involving laser scanner intensity data. The major problem with these methods is misdetection. To minimize this, we mask areas in which target persons should not exist on occupancy grid maps. Target candidates detected in masked areas are rejected, which indicates the possibility of using accurate occupancy grid maps as a user-friendly graphical interface. This paper focuses on the localization method, the target detection method and autonomous navigation knowledge in common space through the challenge.
机译:本文介绍了一种用于自动移动机器人的导航方法,以及在2013年筑波挑战赛期间通过试运行获得的知识,其主要任务是机器人自动导航到目标并在多个城市地区寻找目标人员。准确的地图是复杂课程本地化的重要工具。我们使用激光扫描仪,陀螺仪辅助测距法和DGPS构建了占用栅格地图制作方法。在试运行中,机器人通过两种方式检测目标牧师-一种涉及图像中的颜色检测,另一种涉及激光扫描仪强度数据。这些方法的主要问题是误检测。为了最大程度地减少这种情况,我们会在占用栅格地图上遮盖目标人员不应该存在的区域。在遮蔽区域中检测到的目标候选被拒绝,这表明使用精确的占用栅格图作为用户友好的图形界面的可能性。通过挑战,本文重点研究了公共空间中的定位方法,目标检测方法和自主导航知识。

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