Safe Decentralized Density Control of Multi-Robot Systems using PDE-Constrained Optimization with State Constraints
It addresses the problem of safe multi-robot coordination under communication and localization limitations, offering a decentralized alternative to centralized methods.
This paper presents a decentralized density controller for multi-robot systems that enforces safety constraints using control barrier functions and models robots as probability densities via the Fokker-Planck equation, validated with simulations and experiments on four quadcopters.
In this paper, we introduce a decentralized optimization-based density controller designed to enforce set invariance constraints in multi-robot systems. By designing a decentralized control barrier function, we derived sufficient conditions under which local safety constraints guarantee global safety. We account for localization and motion noise explicitly by modeling robots as spatial probability density functions governed by the Fokker-Planck equation. Compared to traditional centralized approaches, our controller requires less computational and communication power, making it more suitable for deployment in situations where perfect communication and localization are impractical. The controller is validated through simulations and experiments with four quadcopters.