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A mapping method tolerant to calibration and localization errors based on tilting 2D laser scanner

机译:一种基于倾斜二维激光扫描仪的标定和定位误差的映射方法

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Autonomous mobile machines use onboard sensors for navigation and obstacle avoidance. The accuracy of the sensor data in global frame is however dependent on the localization accuracy of the machine. Simultaneous localization and mapping algorithms (SLAM) are widely used with 3D laser scanners for mapping the world. They use scan matching algorithms to solve the accuracy problem by matching prior sensor data of the environment with the newly acquired data. However matching scans is not always possible. Insufficient amount of prior data or too few features in the scan can prevent the scan matching algorithm from finding a match. Thus it is important that also the mapping algorithm is tolerant to some degree of error in localization and calibration. We present a method for generating obstacle maps from smaller data segments at a time, thus making the mapping system more tolerant to navigation and calibration errors. The obstacle mapping method is tested with modified Avant multipurpose loader.
机译:自主移动机器使用机载传感器进行导航和避障。但是,全局框架中传感器数据的精度取决于机器的定位精度。同时定位和地图绘制算法(SLAM)已与3D激光扫描仪一起广泛用于绘制世界地图。他们使用扫描匹配算法通过将环境的先前传感器数据与新获取的数据进行匹配来解决精度问题。但是,匹配扫描并非总是可能的。先前数据量不足或扫描中的特征太少会阻止扫描匹配算法找到匹配项。因此,重要的是,映射算法还必须容忍定位和校准中的一定程度的误差。我们提出了一种用于一次从较小的数据段生成障碍物地图的方法,从而使地图系统更能容忍导航和校准错误。障碍物映射方法已使用改良的Avant多功能装载机进行了测试。

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