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Concurrent mapping and localization and map matching on autonomous underwater vehicles

机译:自主水下航行器的并发地图定位和地图匹配

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Concerns autonomous underwater vehicle (AUV) navigation by concurrent mapping and localization (CAM). This technique, which has roots in the robotics community, endeavors to build a map of a vehicle's environment by extracting information from objects within it while concurrently using that map to position the vehicle. As presented in this paper, CML relies on accurate vehicle attitude information and target tracking to retard the positional error growth rate. Map matching is an independent, but complementary process to CML. Map matching requires good short-term navigation for the creation of a small, local map. The location of this local map is then identified within a larger reference map, providing a periodic positional reset. The a priori reference map may have been created completely in a previous mission, or earlier in the current mission at a time when the positional uncertainty was comparatively small.
机译:通过并发地图和定位(CAM)来关注自主水下航行器(AUV)导航。这项技术起源于机器人技术社区,它通过从其中的对象中提取信息,同时使用该地图来定位车辆,来努力构建车辆环境的地图。如本文所述,CML依靠准确的车辆姿态信息和目标跟踪来延迟位置误差的增长速度。地图匹配是CML的独立过程,但是互补过程。地图匹配需要良好的短期导航才能创建小的本地地图。然后在较大的参考地图中标识此局部地图的位置,从而提供定期的位置重置。先验参考图可能是在先前的任务中完全创建的,或者在位置不确定性相对较小的时候在当前任务的早期创建的。

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