English

Multi-Robot Decentralized Collaborative SLAM in Planetary Analogue Environments: Dataset, Challenges, and Lessons Learned

Robotics 2026-01-30 v1

Abstract

Decentralized collaborative simultaneous localization and mapping (C-SLAM) is essential to enable multirobot missions in unknown environments without relying on preexisting localization and communication infrastructure. This technology is anticipated to play a key role in the exploration of the Moon, Mars, and other planets. In this article, we share insights and lessons learned from C-SLAM experiments involving three robots operating on a Mars analogue terrain and communicating over an ad hoc network. We examine the impact of limited and intermittent communication on C-SLAM performance, as well as the unique localization challenges posed by planetary-like environments. Additionally, we introduce a novel dataset collected during our experiments, which includes real-time peer-to-peer inter-robot throughput and latency measurements. This dataset aims to support future research on communication-constrained, decentralized multirobot operations.

Keywords

Cite

@article{arxiv.2601.21063,
  title  = {Multi-Robot Decentralized Collaborative SLAM in Planetary Analogue Environments: Dataset, Challenges, and Lessons Learned},
  author = {Pierre-Yves Lajoie and Karthik Soma and Haechan Mark Bong and Alice Lemieux-Bourque and Rongge Zhang and Vivek Shankar Varadharajan and Giovanni Beltrame},
  journal= {arXiv preprint arXiv:2601.21063},
  year   = {2026}
}
R2 v1 2026-07-01T09:24:42.303Z