ICRA 2011 Paper Abstract


Paper TuA103.3

Valencia, Rafael (CSIC-UPC), Andrade-Cetto, Juan (CSIC-UPC), Porta, Josep M (CSIC-UPC)

Path Planning in Belief Space with Pose SLAM

Scheduled for presentation during the Regular Sessions "Autonomous Navigation I" (TuA103), Tuesday, May 10, 2011, 08:50−09:05, Room 3D

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on April 2, 2020

Keywords Motion and Path Planning, SLAM, Autonomous Navigation


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.



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