The maps that are built by standard feature-based simultaneous localization and mapping (SLAM) methods cannot be directly used to compute paths for navigation, unless enriched with obstacle or traversability information, with the consequent increase in complexity. Here, we propose a method that directly uses the Pose SLAM graph of constraints to determine the path between two robot configurations with lowest accumulated pose uncertainty, i.e., the most reliable path to the goal. The method shows improved navigation results when compared with standard path-planning strategies over both datasets and real-world experiments.



Author keywords

autonomous navigation, path planning, simultaneous localization and map building (SLAM)

Scientific reference

R. Valencia, M. Morta, J. Andrade-Cetto and J.M. Porta. Planning reliable paths with Pose SLAM. IEEE Transactions on Robotics, 29(4): 1050-1059, 2013.