A framework for multi-session RGBD SLAM in low dynamic workspace environment
A framework for multi-session RGBD SLAM in low dynamic workspace environment
复制标题
低动态工作空间环境下的多会话 RGBD SLAM 框架
DOI：
10.1016/j.trit.2016.03.009
复制
发表时间：
2016-01-01
影响因子：
5.1
通讯作者：
Wu, Jun
中科院分区：
文献类型：
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作者：
Wang, Yue;Huang, Shoudong;Wu, Jun
由于工作空间不可避免的变化，动态环境中的绘图是自主移动机器人的一项重要任务。在本文中，我们提出了一种低动态环境下的 RGBD SLAM 框架，它可以维护跟踪最新环境的地图。描述环境的主要模型是多会话位姿图，它随着机器人的多次访问而演变。当与这些姿势相对应的 3D 点扫描过时时，图中的姿势将被修剪。当机器人探索新区域时，其姿势将被添加到图表中。因此，当前图中保存的扫描将始终给出最新环境的地图。过时扫描识别模块通过分析不同会话收集的扫描来检测环境的变化。此外，采用冗余扫描识别模块来进一步减少具有冗余扫描的姿势，以相对于环境的大小保持图中的姿势总数。在实验中，首先根据 Kinect 从实验室环境获取的数据对该框架进行调整和测试。然后将该框架应用于Kinect II从另一个国家的工业机器人工作空间获取的外部数据集（该数据集不了解开发阶段），以进一步验证性能。经过两步评估后，所提出的框架被认为能够在动态或静态环境中以非累积复杂性和可接受的错误水平管理最新的地图。版权所有(C)2016，重庆工业大学。由 Elsevier B.V. 制作和主持
Mapping in the dynamic environment is an important task for autonomous mobile robots due to the unavoidable changes in the workspace. In this paper, we propose a framework for RGBD SLAM in low dynamic environment, which can maintain a map keeping track of the latest environment. The main model describing the environment is a multi-session pose graph, which evolves over the multiple visits of the robot. The poses in the graph will be pruned when the 3D point scans corresponding to those poses are out of date. When the robot explores the new areas, its poses will be added to the graph. Thus the scans kept in the current graph will always give a map of the latest environment. The changes of the environment are detected by out-of-dated scans identification module through analyzing scans collected at different sessions. Besides, a redundant scans identification module is employed to further reduce the poses with redundant scans in order to keep the total number of poses in the graph with respect to the size of environment. In the experiments, the framework is first tuned and tested on data acquired by a Kinect from laboratory environment. Then the framework is applied to external dataset acquired by a Kinect II from a workspace of an industrial robot in another country, which is blind to the development phase, for further validation of the performance. After this two-step evaluation, the proposed framework is considered to be able to manage the map in date in dynamic or static environment with a noncumulative complexity and acceptable error level. Copyright (C) 2016, Chongqing University of Technology. Production and hosting by Elsevier B.V.