ROMAN: Open-Set Object Map Alignment for Robust View-Invariant Global Localization

Mason Peterson1, Yi Xuan Jia1, Yulun Tian1,2, Annika Thomas1, Jonathan How1
1Massachusetts Institute of Technology 2University of California, San Diego
arXiv Code Data
Example Image

Pair of segment submaps matched by two robots traveling in opposite directions in an off-road environment. Associated segments found by the proposed method are connected by lines and projected onto the image plane. (Top) Each pair of associated segments is drawn with the same color. The remaining, unmatched segments are shown in random colors and all other background points are shown in gray. (Bottom) The same associated segments and their convex hulls are visualized in the original image observations.

Abstract

Global localization is a fundamental capability required for long-term and drift-free robot navigation. However, current methods fail to relocalize when faced with significantly different viewpoints. We present ROMAN (Robust Object Map Alignment Anywhere), a robust global localization method capable of localizing in challenging and diverse environments based on creating and aligning maps of open-set and view-invariant objects. To address localization difficulties caused by feature-sparse or perceptually aliased environments, ROMAN formulates and solves a registration problem between object submaps using a unified graph-theoretic global data association approach that simultaneously accounts for object shape and semantic similarities and a prior on gravity direction. Through a set of challenging large-scale multi-robot or multi-session SLAM experiments in indoor, urban and unstructured/forested environments, we demonstrate that ROMAN achieves a maximum recall 36% higher than other object-based map alignment methods and an absolute trajectory error that is 37% lower than using visual features for loop closures.

BibTeX

@article{peterson2024roman,
  author    = {Peterson, Mason and Jia, Yi Xuan and Tian, Yulun and Thomas, Annika and How, Jonathan},
  title     = {ROMAN: Open-Set Object Map Alignment for Robust View-Invariant Global Localization},
  journal   = {arXiv preprint arXiv:2410.08262},
  year      = {2024},
}