SKiD-SLAM: Resource-Aware Distributed Multirobot LiDAR SLAM for Planetary Missions With Field Deployments at Analog Sites
Abstract
In future planetary exploration missions, teams of robots will need to collaboratively build maps in unknown environments, from subsurface caves and lava tubes to crater-strewn surface terrains. Such collaboration enables faster and more robust mapping than a single robot can achieve by sharing observations and computation across the team. However, this collaboration typically assumes seamless communication and abundant computing resources, whereas planetary environments impose severe communication limits, constrained onboard computation, and the absence of any central infrastructure. In this field report, we present SKiD-SLAM, a distributed multirobot light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) system for such communication-constrained planetary environments, and report its deployment across two representative mission concepts, i.e., 1) cave exploration and 2) scientific surface exploration. To build the system, we survey the communication and computation budgets of actual planetary missions, and select modules that fit these budgets for each core function of distributed multirobot LiDAR SLAM. These core functions are recognizing revisited places across robots’ maps, estimating inter-robot relative poses, and fusing trajectories without a central server. Before field deployment, we verify the assembled system on public datasets that resemble planetary environments and in a simulator built on the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL)’s Open Source Rover (OSR). We then validate our SKiD-SLAM in both mission concepts through field deployments in South Korea, where 1) a team of wheeled rovers explores the Majang lava-tube cave on Jeju Island, and 2) quadruped robots carry out a crater-and-rock science scenario on a planetary analog terrain at Korea Institute of Civil Engineering and Building Technology (KICT) in Yeoncheon. Across both deployments, our SKiD-SLAM reliably performed distributed multirobot LiDAR SLAM within the 250-kbps inter-robot communication budget, demonstrating its feasibility under challenging field conditions. The supplementary materials, including our code and field data, are publicly available at https://sparolab.github.io/research/skid_slam/