Proving the existence of loops in robot trajectories
This provides a reliable loop closure detection method for SLAM in challenging environments like underwater exploration, improving localization and mapping with reduced computing burden.
The paper tackles the problem of verifying loops in robot trajectories under uncertainty using proprioceptive measurements, and demonstrates that a method based on topological degree is optimal for proving loops, validated on real autonomous underwater vehicle datasets.
This paper presents a reliable method to verify the existence of loops along the uncertain trajectory of a robot, based on proprioceptive measurements only, within a bounded-error context. The loop closure detection is one of the key points in SLAM methods, especially in homogeneous environments with difficult scenes recognitions. The proposed approach is generic and could be coupled with conventional SLAM algorithms to reliably reduce their computing burden, thus improving the localization and mapping processes in the most challenging environments such as unexplored underwater extents. To prove that a robot performed a loop whatever the uncertainties in its evolution, we employ the notion of topological degree that originates in the field of differential topology. We show that a verification tool based on the topological degree is an optimal method for proving robot loops. This is demonstrated both on datasets from real missions involving autonomous underwater vehicles, and by a mathematical discussion.