Above and Below: Heterogeneous Multi-Robot SLAM across Surface and Underwater Domains
John McConnell, Armon Shariati, Paul Szenher, Yaxuan Li
AI summary
Problem
Multi-robot SLAM between surface vessels and underwater vehicles typically relies on acoustic pinging, which fails in cluttered maritime environments due to signal blockage, proximity requirements, and clock synchronization needs.
Approach
The system detects indirect loop closures by matching compressed underwater sonar contacts with above-water LiDAR scans, merging independent robot pose graphs into a centralized, unified trajectory and map.
Key results
- First USV-AUV multi-robot SLAM system using indirect perceptual loop closures
- Bandwidth-efficient sonar compression method preserving cell resolution
- Improved AUV localization accuracy over single-robot SLAM in three real-world environments
- Open-source code and dataset release for marine robotics research
Why it matters
Provides a reliable, communication-efficient navigation framework for heterogeneous marine robot teams operating in complex littoral zones where acoustic signals are unreliable.
Abstract
Multi-robot simultaneous localization and mapping (SLAM) is a fundamental task in multi-robot operations. Robots must have a common understanding of their location and that of their team members to complete coordinated actions. However, multi-robot SLAM between Uncrewed Surface Vessels (USVs) and Autonomous Underwater Vehicles (AUVs) has primarily been achieved through acoustic pinging between robots to re- trieve range measurements; a measurement technique requires that robots to be in similar locations simultaneously, have an uninterrupted path for signal propagation, and may necessitate synchronized clocks. This is especially challenging in complex, cluttered maritime environments, where structures may impede signals. However, these same structures may be observable above and below the water’s surface, presenting an opportunity for inter-robot SLAM loop closure between USV and AUV data streams. This work builds upon recent research on inter-robot SLAM loop closure between USV and AUV data [4], extending it to propose a centralized multi-robot SLAM system. Each robot performs its state estimation, and we detect loop closures between each AUV and the USV data. These inter-robot loop closures are used to merge each robot’s state estimate into a centralized graph, yielding estimates for the whole time history of the USV and all AUVs in the system. Validation is performed using real- world perceptual data in three different environments. Results show improved errors for AUVs in the multi-robot SLAM system compared to single-robot SLAM over the same trajectories. To our knowledge, this is the first instance of a multi-robot SLAM system with AUVs and USVs built on loop closures rather than acoustic distance measurements. The views expressed in this document are those of the author(s) and do not reflect the official policy or position of the U.S. Naval Academy, Department of the Navy, the Department of Defense, or the U.S. Government.