Path Planning in Belief Space with Pose SLAM

摘要：

The probabilistic belief networks that result from standard feature-based simultaneous localization and map building cannot be directly used to plan trajectories. The reason is that they produce a sparse graph of landmark estimates and their probabilistic relations, which is of little value to find collision free paths for navigation. In contrast, we argue in this paper that Pose SLAM graphs can be directly used as belief roadmaps. We present a method that devises optimal navigation strategies by searching for the path in the pose graph with lowest accumulated robot pose uncertainty, independently of the map reference frame. The method shows improved navigation results when compared to shortest paths both over synthetic data and real datasets.

作者: Rafael Valencia Juan Andrade-Cetto Josep M. Porta

作者单位: Institut de Rob(o)tica i Inform(a)tica Industrial,CSIC-UPC,Llorens Artigas 4-6,Barcelona 08028,Spain

会议类型: 国际会议

会议名称: 2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

会议地点: 上海

会议语种:英文

页码: 78-83

在线出版日期: 2011-05-09（万方平台首次上网日期，不代表论文的发表时间）