Multi-Robot Active Information Gathering with Periodic Communication
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Abstract (arXiv)
A team of robots sharing a common goal can benefit from coordination of the activities of team members, helping the team to reach the goal more reliably or quickly. We address the problem of coordinating the actions of a team of robots with periodic communication capability executing an information gathering task. We cast the problem as a multi-agent optimal decision-making problem with an information theoretic objective function. We show that appropriate techniques for solving decentralized partially observable Markov decision processes (Dec-POMDPs) are applicable in such information gathering problems. We quantify the usefulness of coordinated information gathering through simulation studies, and demonstrate the feasibility of the method in a real-world target tracking domain.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Mar 2017.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 0; 2025: 0; 2026: 2.
3 papers.
- 2022Partially Observable Markov Decision Processes in Robotics: A Surveycited by 81
- 2026Cooperative Informative Sensing for Monitoring Dynamic Indoor Environments via Multi-Agent Reinforcement Learningcited by 0
- 2026WONDER: A Radio World Model-based Negotiation Framework for Multi-Agent UAV Coverage Optimizationcited by 0
- 2026WONDER: A Radio World Model-based Negotiation Framework for Multi-Agent UAV Coverage Optimization16 Aug 2026
- 2026Cooperative Informative Sensing for Monitoring Dynamic Indoor Environments via Multi-Agent Reinforcement Learning25 Apr 2026
- 2022Partially Observable Markov Decision Processes in Robotics: A Survey21 Sep 2022