Multi-robot LiDAR SLAM: a practical case study in underground tunnel environments

TL;DR

This paper analyzes decentralized multi-robot LiDAR SLAM in underground tunnels, identifies false positives in loop detection as a key failure source, and proposes a heuristic to improve robustness in such challenging environments.

Contribution

It introduces a new heuristic to mitigate false positives in loop detection for multi-robot LiDAR SLAM in underground tunnels.

Findings

Loop detection causes many false positives in current systems.

The proposed heuristic reduces false positives and improves SLAM robustness.

Underground tunnels present unique challenges for multi-robot SLAM.

Abstract

Multi-robot SLAM aims at localizing and building a map with multiple robots, interacting with each other. In the work described in this article, we analyze the pipeline of a decentralized LiDAR SLAM system to study the current limitations of the state of the art, and we discover a significant source of failures, i.e., that the loop detection is the source of too many false positives. We therefore develop and propose a new heuristic to overcome these limitations. The environment taken as reference in this work is the highly challenging case of underground tunnels. We also highlight potential new research areas still under-explored.