Meeting-Merging-Mission: A Multi-robot Coordinate Framework for Large-Scale Communication-Limited Exploration
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Abstract (arXiv)
This letter presents a complete framework Meeting-Merging-Mission for multi-robot exploration under communication restriction. Considering communication is limited in both bandwidth and range in the real world, we propose a lightweight environment presentation method and an efficient cooperative exploration strategy. For lower bandwidth, each robot utilizes specific polytopes to maintains free space and super frontier information (SFI) as the source for exploration decision-making. To reduce repeated exploration, we develop a mission-based protocol that drives robots to share collected information in stable rendezvous. We also design a complete path planning scheme for both centralized and decentralized cases. To validate that our framework is practical and generic, we present an extensive benchmark and deploy our system into multi-UGV and multi-UAV platforms.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Sep 2021.
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Citing papers per year: 2023: 1; 2024: 3; 2025: 1.
5 papers.
- 2024ActiveGS: Active Scene Reconstruction Using Gaussian Splattingcited by 34
- 2025Large Language Models for Multi-Robot Systems: A Surveycited by 26
- 2023PIMbot: Policy and Incentive Manipulation for Multi-Robot Reinforcement Learning in Social Dilemmascited by 4
- 2024Communication- and Computation-Efficient Distributed Submodular Optimization in Robot Mesh Networkscited by 2
- 2024PRIMER: Perception-Aware Robust Learning-based Multiagent Trajectory Plannercited by 0
- 2025Large Language Models for Multi-Robot Systems: A Survey6 Feb 2025
- 2024ActiveGS: Active Scene Reconstruction Using Gaussian Splatting23 Dec 2024
- 2024Communication- and Computation-Efficient Distributed Submodular Optimization in Robot Mesh Networks15 Jul 2024
- 2024PRIMER: Perception-Aware Robust Learning-based Multiagent Trajectory Planner14 Jun 2024
- 2023PIMbot: Policy and Incentive Manipulation for Multi-Robot Reinforcement Learning in Social Dilemmas29 Jul 2023