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cs.RO2026
From Discrete Plans to Real-World Execution: A World-Model-Driven Framework for Execution-Aware Multi-Agent Path Finding
Jingtian Yan, Shuai Zhou, He Jiang +2
Multi-Agent Path Finding (MAPF) studies how to coordinate multiple agents to reach their goals without collisions and underpins a range of large-scale robotic systems, including au…
cs.RO2026
Advancing MAPF Toward the Real World: A Scalable Multi-Agent Realistic Testbed (SMART)
Jingtian Yan, Zhifei Li, William Kang +7
We present Scalable Multi-Agent Realistic Testbed (SMART), a realistic and efficient software tool for evaluating Multi-Agent Path Finding (MAPF) algorithms. MAPF focuses on planni…