文章基本信息

标题：Spatio-temporal voxel layer: A view on robot perception for the dynamic world
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作者：This article is part of the following special collection
期刊名称：International Journal of Advanced Robotic Systems
印刷版ISSN：1729-8806
电子版ISSN：1729-8814
出版年度：2020
卷号：17
期号：2
页码：1-14
DOI：10.1177/1729881420910530
出版社：SAGE Publications
摘要：The spatio-temporal voxel grid is an actively maintained open-source project providing an improved three-dimensional environmental representation that has been garnering increased adoption in large, dynamic, and complex environments. We provide a voxel grid and the Costmap 2-D layer plug-in, Spatio-Temporal Voxel Layer, powered by a real-time sparse occupancy grid with constant time access to voxels which does not scale with the environment’s size. We replace ray-casting with a new clearing technique we dub frustum acceleration that does not assume a static environment and in practice, represents moving environments better. Our method operates at nearly 400% less CPU load on average while processing 9 QVGA resolution depth cameras as compared to the voxel layer. This technique also supports sensors such as three-dimensional laser scanners, radars, and additional modern sensors that were previously unsupported in the available ROS Navigation framework that has become staples in the roboticists’ toolbox. These sensors are becoming more widely used in robotics as sensor prices are driven down and mobile compute capabilities improve. The Spatio-Temporal Voxel Layer was developed in the open with community feedback over its development life cycle and continues to have additional features and capabilities added by the community. As of February 2019, the Spatio-Temporal Voxel Layer is being used on over 600 robots worldwide in warehouses, factories, hospitals, hotels, stores, and libraries. The open-source software can be viewed and installed on its GitHub page at https://github.com/SteveMacenski/spatio_temporal_voxel_layer ..
关键词：Mobile robots ; perception ; OpenVDB ; frustum ; frustum acceleration ; open;source ; ROS ; dynamic environments ; navigation