Key Concepts
- Centralized vs Decentralized — Single server vs peer-to-peer map merging
- Inter-robot loop closure — Place recognition across robots with different viewpoints
- Communication constraints — Bandwidth-limited map sharing, sparse descriptors
- Map merging — Aligning submaps from different robots into a global map
Systems
| System | Author/Year | Key Concepts |
|---|---|---|
| C2TAM | Riazuelo 2014 | Cloud-based collaborative monocular SLAM |
| CCM-SLAM | Schmuck & Chli 2019 | Centralized collaborative monocular SLAM, robust to comm failures |
| DOOR-SLAM | Lajoie 2020 | Distributed, outlier-resilient SLAM with pairwise consistency |
| Kimera-Multi | Tian 2022 | Distributed multi-robot metric-semantic SLAM, mesh reconstruction |
| Swarm-SLAM | Lajoie 2024 | Decentralized, sparse, scalable C-SLAM, supports LiDAR/stereo/RGB-D |
| CoPeD | Zhou 2024 | Multi-robot collaborative perception dataset (real-world, aerial + ground robots) |
| maplab 2.0 | Cramariuc 2023 | Multi-session, multi-robot visual-inertial mapping |