GuardPIBT: Counterfactually Gated Neural Guidance for Ultra-Large-Scale 3D Multi-Agent Path Finding

Yuan Zhou; Zhenyu Hou; Guangtong Xu; Xiaoqiang Ji; Yuqing Tang; Jialiang Hou; Fei Gao

cs.ROSep 28, 2026

GuardPIBT: Counterfactually Gated Neural Guidance for Ultra-Large-Scale 3D Multi-Agent Path Finding

Authors: Yuan Zhou, Zhenyu Hou, Guangtong Xu, Xiaoqiang Ji, Yuqing Tang, Jialiang Hou, Fei Gao

Organizations: Institute of Cyber-Systems and Control, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China. · Differential Robotics Technology Company, Hangzhou 311121, China. · Huzhou Institute, Zhejiang University, Huzhou 313000, China. · School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China. · School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China. · International Digital Economy Academy, Shenzhen, Guangdong, China.

Abstract

Large-scale 3D multi-agent path finding becomes increasingly difficult under dense traffic. Priority Inheritance with Backtracking (PIBT) scales well, but its one-step goal-directed ordering may become insufficient under dense interactions and large-scale congestion. We present GuardPIBT, which augments rather than replaces the PIBT executor: neural predictions only propose residual reorderings of PIBT's native candidates, while final actions remain determined by PIBT. First, local graph attention models nearby interactions, while global source--goal transport features provide population-level coordination context for candidate reordering. Second, a counterfactual group gate filters reorderings whose closed-loop effects may degrade coordination. Third, for ultra-large populations, population-adaptive grouping preserves decision granularity, asynchronous cached inference amortizes neural computation, and selective repair resolves long-tail agents. PIBT retains validity checking, priority inheritance, and backtracking throughout. Experiments with up to 100,000 agents demonstrate reliable completion across 2D and 3D environments, including all three 100,000-agent warehouse runs with zero audited graph violations. The project website is available at {\color{magenta}\texttt{https://guardpibt.github.io/GuardPIBT/}}.

Figures & tables

Fig. 1: Overview of GuardPIBT for ultra-large-scale MAPF. (a) 1000000 agents in gate obstacles. (b) 100000 agents in 2D maze. (c) 100000 agents in gate obstacles.

Fig. 2: GuardPIBT pipeline: global–local candidate scoring, executor-aligned group gating, and scalable deployment with adaptive grouping, asynchronous inference, and selective tail repair.

Scene	Metric	$N=100$				$N=1{,}000$				$N=10{,}000$
Scene	Metric	Guard PIBT	LaCAM	PyPIBT	LaGAT	Guard PIBT	LaCAM	PyPIBT	LaGAT	Guard PIBT	LaCAM	PyPIBT	LaGAT
Forest	$T_{\mathrm{E2E}}(\mathrm{s})$ $\bar{C}_{\mathrm{SOC}}$	6.24 18.93	0.02 24.58	0.28 24.36	8.12 20.78	14.31 63.68	0.49 91.96	– –	10.75 72.74	172.41 241.33	– –	– –	386.40 249.77
Maze	$T_{\mathrm{E2E}}(\mathrm{s})$ $\bar{C}_{\mathrm{SOC}}$	6.24 26.82	0.02 36.98	0.28 35.44	8.05 28.39	16.36 275.61	0.57 289.90	178.17 374.69	54.21 224.24	113.53 2051.33	174.89 2910.90	– –	– –
Warehouse	$T_{\mathrm{E2E}}(\mathrm{s})$ $\bar{C}_{\mathrm{SOC}}$	6.61 22.06	0.02 28.47	0.29 29.18	8.04 23.75	8.96 70.72	0.38 99.58	12.378 99.67	10.269 77.38	168.936 315.67	39.64 394.87	888.188 394.93	257.24 288.04

TABLE I: Scalability comparison on 2D Forest, Maze, and Warehouse scenes.

Fig. 3: Cross-scene generalization of GuardPIBT across diverse 2D and 3D environments. (a)–(d) correspond to a 2D random forest, 2D warehouse, 3D gate walls, and maze, respectively.

Fig. 4: Cross-scene generalization of GuardPIBT

Fig. 5: Snapshots of a $100{,}000$ -agent Warehouse-3D run from initialization through dense coordination to final completion.

Metric	F-2D	M-2D	W-2D	GW-3D	W-3D
$T_{\mathrm{E2E}}$ (s)	1104.83	5208.15	1163.11	194.61	908.61
$\bar{C}_{\mathrm{SOC}}$	2573.77	16558.92	2228.62	659.31	1041.83

TABLE II: 100k-agent cross-scene results. F/M/W denote Forest/Maze/Warehouse; GW denote Gate Walls.

Variant	$T_{\mathrm{E2E}}$ (s)	$\bar{C}_{\mathrm{SOC}}$	$\bar{W}_{\mathrm{step}}$
GuardPIBT	256.10	3739.17	2192.83
W/o global flow	251.45	4089.50	2521.93
W/o CF gate	250.34	3772.39	2205.99

TABLE III: Core mechanism ablation on the

10{,}000

-agent 3D warehouse.

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Abstract

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