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New PUSH planner enables scalable long-horizon pathfinding for thousands of agents

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced PUSH (Path Updates over Staggered Horizons), a novel planner designed for Lifelong Multi-Agent Path Finding (LMAPF). PUSH aims to overcome the limitations of existing reactive frameworks by enabling long-horizon reasoning while maintaining scalability for thousands of agents. The system combines elements from PIBT, RHCR, and TP, allowing it to plan over multi-step horizons on general maps without restrictive assumptions, and has demonstrated significant throughput improvements in evaluations. AI

IMPACT This new planning approach could enable more efficient coordination of large-scale robotic fleets and autonomous systems.

RANK_REASON The cluster contains a research paper detailing a new algorithm for multi-agent pathfinding.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New PUSH planner enables scalable long-horizon pathfinding for thousands of agents

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Vaibhav Sanjay, Jiaoyang Li ·

    Scalable Long-Horizon Planning with Staggered Updates for Lifelong MAPF

    arXiv:2608.06702v1 Announce Type: cross Abstract: Lifelong Multi-Agent Path Finding (LMAPF) requires generating collision-free paths for large agent fleets under strict real-time constraints. Reactive frameworks such as PIBT and Enhanced PIBT (EPIBT) scale effortlessly to thousan…

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Jiaoyang Li ·

    Scalable Long-Horizon Planning with Staggered Updates for Lifelong MAPF

    Lifelong Multi-Agent Path Finding (LMAPF) requires generating collision-free paths for large agent fleets under strict real-time constraints. Reactive frameworks such as PIBT and Enhanced PIBT (EPIBT) scale effortlessly to thousands of agents through rule-based, step-by-step coor…

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