Forecast-Driven MPC for Decentralized Multi-Robot Collision Avoidance
The Iterative Forecast Planner (IFP) is a geometric planning approach that offers lightweight computations, scal- able, and reactive solutions for multi-robot path planning in decentralized, communication-free settings. However, it struggles in symmetric configurations, where mirrored interactions often lead to collisions and deadlocks. We introduce eIFP-MPC, an optimized and extended version of IFP that improves robustness and path consistency in dense, dynamic environments. The method refines…
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