# Decentralized Ergodic Control: Distribution-Driven Sensing and Exploration for Multi-Agent Systems

arXiv: https://arxiv.org/abs/1806.05220 · HTML: https://mlsanity.com/paper/1806.05220/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jun 2018.

## Built on by (most cited first, 4 of 4)

- [Fast Ergodic Search with Kernel Functions](https://mlsanity.com/paper/2403.01536/) (2024)
- [Flow Matching Ergodic Coverage](https://mlsanity.com/paper/2504.17872/) (2025)
- [Volumetric Ergodic Control](https://mlsanity.com/paper/2511.11533/) (2025)
- [BOIL: Learning Environment Personalized Information](https://mlsanity.com/paper/2604.17137/) (2026)

## Abstract (arXiv)

We present a decentralized ergodic control policy for time-varying area coverage problems for multiple agents with nonlinear dynamics. Ergodic control allows us to specify distributions as objectives for area coverage problems for nonlinear robotic systems as a closed-form controller. We derive a variation to the ergodic control policy that can be used with consensus to enable a fully decentralized multi-agent control policy. Examples are presented to illustrate the applicability of our method for multi-agent terrain mapping as well as target localization. An analysis on ergodic policies as a Nash equilibrium is provided for game theoretic applications.