Swarm-SLAM : Sparse Decentralized Collaborative Simultaneous Localization and Mapping Framework for Multi-Robot Systems
About
Collaborative Simultaneous Localization And Mapping (C-SLAM) is a vital component for successful multi-robot operations in environments without an external positioning system, such as indoors, underground or underwater. In this paper, we introduce Swarm-SLAM, an open-source C-SLAM system that is designed to be scalable, flexible, decentralized, and sparse, which are all key properties in swarm robotics. Our system supports inertial, lidar, stereo, and RGB-D sensing, and it includes a novel inter-robot loop closure prioritization technique that reduces communication and accelerates convergence. We evaluated our ROS-2 implementation on five different datasets, and in a real-world experiment with three robots communicating through an ad-hoc network. Our code is publicly available: https://github.com/MISTLab/Swarm-SLAM
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Tracking | AriaMultiagent | ATE RMSE4.29 | 30 | |
| SLAM Tracking | ReplicaMultiagent | Off-0 Score1.76 | 15 | |
| Trajectory tracking | Multi-agent Replica Apartment-1 | ATE RMSE (cm)4.62 | 15 | |
| Trajectory tracking | Multi-agent Replica Office-0-C | ATE RMSE (cm)1.07 | 15 | |
| Trajectory tracking | Multi-agent Replica Apartment-2 | ATE RMSE (cm)2.69 | 15 | |
| Trajectory tracking | Multi-agent Replica Apartment-0 | ATE RMSE (cm)1.61 | 12 | |
| Trajectory tracking | Multi-agent Replica Average | ATE RMSE (cm)2.5 | 12 | |
| SLAM | S3E Campus sequence | Sequence Length (N)29 | 9 | |
| SLAM | S3E Teaching sequence | Sequence Length (N)110 | 9 | |
| SLAM | S3E Square sequence | Sequence Length (N)7 | 9 |