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Consistency Based Error Evaluation for Deep Sea Bathymetric Mapping with Robotic Vehicles

机译:基于一致性的机器人车辆深海浴游图的误差评估

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This paper presents a method to evaluate the mapping error present in point cloud terrain maps created using robotic vehicles and range sensors. This work focuses on mapping environments where no a priori ground truth is available and self consistency is the only available check against false artifacts and errors. The proposed error measure is based on a disparity measurement between common sections of the environment that have been imaged multiple times. This disparity measure highlights inconsistency in the terrain map by showing regions where multiple overlapping point clouds do not fit together well. This error measure provides the map interpreter with a localized error measurement to help judge the validity of the final point cloud or gridded surface. It is shown that the proposed method highlights mapping errors more clearly than a principle component based measure used in the 3D modelling community. Results are presented for bathymetric mapping over natural terrain in the deep ocean using a remotely operated vehicle (ROV) outfitted with navigation sensors and a multibeam sonar system.
机译:本文提出了一种评估使用机器人车辆和范围传感器创建的点云地形映射中存在的映射错误的方法。这项工作侧重于映射环境,其中没有先验的地面真理,自我一致性是唯一可用的针对虚假工件和错误的检查。所提出的错误测量基于已经多次成像的环境的公共部分之间的视差测量。这种差异测量通过显示多个重叠点云不适合的区域来突出地形图中的不一致。此错误测量为地图解释器提供了本地化的错误测量,以帮助判断最终点云或网格表面的有效性。结果表明,该方法比3D建模社区中使用的主要组件的措施更清楚地突出显示映射误差。使用带有导航传感器的远程操作的车辆(ROV)和多滨声纳系统,提供了在深海天然地形上的碱基测绘的结果。

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