LLLG extends LaCAM with local guidance to lifelong MAPF using windowed planning and warm-starts, claiming higher throughput than prior planners in dense environments.
Iterative Refinement for Real-Time Multi-Robot Path Planning , year =
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2representative citing papers
An alternating target-path planning framework decouples assignment from pathfinding in TAPF and uses MAPF feedback to iteratively refine assignments, scaling beyond CBS solvers.
citing papers explorer
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Lifelong LaCAM with Local Guidance for Lifelong MAPF
LLLG extends LaCAM with local guidance to lifelong MAPF using windowed planning and warm-starts, claiming higher throughput than prior planners in dense environments.
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Alternating Target-Path Planning for Scalable Multi-Agent Coordination
An alternating target-path planning framework decouples assignment from pathfinding in TAPF and uses MAPF feedback to iteratively refine assignments, scaling beyond CBS solvers.