Safe and Energy-Aware Multi-Robot Density Control via PDE-Constrained Optimization for Long-Duration Autonomy
Longchen Niu, Andrew Nasif, Gennaro Notomista
TLDR
This paper introduces a novel PDE-constrained optimization framework for safe and energy-aware multi-robot density control, ensuring long-duration autonomy.
Key contributions
- Novel density control framework for multi-robot systems with spatial safety and energy sustainability.
- Models stochastic robot motion using Fokker-Planck PDEs for density-level control.
- Integrates CLFs/CBFs with PDEs to ensure target density, obstacle avoidance, and energy sufficiency.
- Employs a quadratic program for fast, real-time command adjustments and in-the-loop implementation.
Why it matters
This paper addresses critical challenges in multi-robot systems: ensuring safety and energy sustainability for long-duration missions. By providing guarantees through a PDE-constrained optimization approach, it enables more robust and reliable autonomous operations. The real-time implementation makes it practical for complex, uncertain environments.
Original Abstract
This paper presents a novel density control framework for multi-robot systems with spatial safety and energy sustainability guarantees. Stochastic robot motion is encoded through the Fokker-Planck Partial Differential Equation (PDE) at the density level. Control Lyapunov and control barrier functions are integrated with PDEs to enforce target density tracking, obstacle region avoidance, and energy sufficiency over multiple charging cycles. The resulting quadratic program enables fast in-the-loop implementation that adjusts commands in real-time. Multi-robot experiment and extensive simulations were conducted to demonstrate the effectiveness of the controller under localization and motion uncertainties.
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