Decentralized Ergodic Control: Distribution-Driven Sensing and Exploration for Multi-Agent Systems
This work addresses area coverage challenges in multi-agent robotics, offering a decentralized solution that is incremental over existing ergodic control methods.
The paper tackles the problem of time-varying area coverage for multi-agent systems with nonlinear dynamics by introducing a decentralized ergodic control policy, which enables agents to specify distributions as objectives and operate without central coordination, with examples shown for terrain mapping and target localization.
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.