# Multi-Robot Active Information Gathering with Periodic Communication

arXiv: https://arxiv.org/abs/1703.02610 · HTML: https://mlsanity.com/paper/1703.02610/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Mar 2017.

## Built on by (most cited first, 3 of 3)

- [Partially Observable Markov Decision Processes in Robotics: A Survey](https://mlsanity.com/paper/2209.10342/) (2022)
- [Cooperative Informative Sensing for Monitoring Dynamic Indoor Environments via Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/2604.23179/) (2026)
- [WONDER: A Radio World Model-based Negotiation Framework for Multi-Agent UAV Coverage Optimization](https://mlsanity.com/paper/2608.16955/) (2026)

## 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.