DRACO-SLAM2

This repository accompanies the paper DRACo-SLAM2: Distributed Robust Acoustic Communication-efficient SLAM for Imaging Sonar Equipped Underwater Robot Teams with Object Graph Matching (IROS 2025).

DRACo-SLAM2 is a distributed SLAM framework for underwater robot teams equipped with imaging sonar. This framework improves upon the original DRACo-SLAM by introducing a novel representation of sonar maps as object graphs and utilizing object graph matching to achieve time-efficient inter-robot loop closure detection without relying on prior geometric information. To better-accommodate the needs and characteristics of underwater scan matching, we propose incremental Group-wise Consistent Measurement Set Maximization (GCM), a modification of Pairwise Consistent Measurement Set Maximization (PCM), which effectively handles scenarios where nearby inter-robot loop closures share similar registration errors.

• Overview of DRACo-SLAM2 Architecture:
  • The local robot:
    • Groups nearby feature points into an object map using DBSCAN.
    • Receives a neighboring robot’s object map.
    • Aligns the received map with its own via graph matching.
    • Requests raw scans from the neighbor for ICP registration, using the graph matching transformation as an initial guess.
    • Adds inter-robot loop closures to the pose graph.
    • A two-step pose graph optimization (PGO) is performed to refine the global estimate.
  • The multi-robot component is currently decoupled from the single-robot SLAM system. We encourage you to integrate the multi-robot code with your own single-robot SLAM front-end — any implementation is welcome and appreciated.

  ├──DRACO2
     ├── config                     # Parameters fpr DRACO1 & DRACO2
     ├── SLAM                       # Both DRACO1 & DRACO2 SLAM code
     ├── scripts
     │   └── run_mission.py         # Multi-robot SLAM example
     ├── data                       # Folder for the dataset
     └── ...

• Example DRACo-SLAM2 result with real sonar data collected at the U.S. Merchant Marine Academy, King’s Point, NY, aligned with a satellite image.

Dependencies

• BRUCE-SLAM
• We provide there example datasets.

How to use

cd FOLDER_BRUCE_SLAM
source /opt/ros/noetic/setup.sh
source devel/setup.sh
python FOLDER_DRACO2/scripts/run_mission.py -b PATH_TO_BAG -p PATH_TO_PICKLE -y config/param.yaml -o PATH_TO_OUTPUT
# bag file not needed for real-world example in our case