It Takes Two to Tango: A Holistic Simulator for Joint Order Scheduling and Multi-Agent Path Finding in Robotic Warehouses

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Authors: Haozheng Xu, Wenhao Li, Zifan Wei, Bo Jin, Hongxing Bai, Ben Yang, Xiangfeng Wang
Cited by: 0

Abstract

The prevailing paradigm in Robotic Mobile Fulfillment Systems (RMFS) typically treats order scheduling and multi-agent pathfinding as isolated sub-problems. We argue that this decoupling is a fundamental bottleneck, masking the critical dependencies between high-level dispatching and low-level congestion. Existing simulators fail to bridge this gap, often abstracting away heterogeneous kinematics and stochastic execution failures. We propose WareRover, a holistic simulation platform that enforces a tight coupling between OS and MAPF via a unified, closed-loop optimization interface. Unlike standard benchmarks, WareRover integrates dynamic order streams, physics-aware motion constraints, and non-nominal recovery mechanisms into a single evaluation loop. Experiments reveal that SOTA algorithms often falter under these realistic coupled constraints, demonstrating that WareRover provides a necessary and challenging testbed for robust, next-generation warehouse coordination. The project and video is available at https://hhh-x.github.io/WareRover/.

Fields of Study & Subjects

Advanced Manufacturing and Logistics Optimization Robotic Path Planning Algorithms Scheduling and Optimization Algorithms

Publication details

Journal / source
arXiv (Cornell University)
Publication date
15 February 2026
Language
EN
Document type
Preprint