collaborators

5 papers

cs.RO2026

Dual-Informed Vertical Expansion for Multi-Objective Node Selection in Anytime Conflict-Based Search

Willem van Osselaer, Jiarui Li, Meshal Alharbi +1

Conflict-Based Search (CBS) is a leading exact algorithm for Multi-Agent Path Finding (MAPF), but its high-level node-selection rule is usually treated as a fixed implementation de…

cs.RO2026

Adaptive-Horizon Conflict-Based Search for Closed-Loop Multi-Agent Path Finding

Jiarui Li, Federico Pecora, Runyu Zhang +1

Multi-Agent Path Finding (MAPF) is a core coordination problem for large robot fleets in automated warehouses and logistics. Existing approaches are typically either open-loop plan…

cs.RO2026

Certificate-Driven Closed-Loop Multi-Agent Path Finding with Inheritable Factorization

Jiarui Li, Runyu Zhang, Gioele Zardini

Multi-agent coordination in automated warehouses and logistics is commonly modeled as the Multi-Agent Path Finding (MAPF) problem. Closed-loop MAPF algorithms improve scalability b…

cs.RO2026

FICO: Finite-Horizon Closed-Loop Factorization for Unified Multi-Agent Path Finding

Jiarui Li, Alessandro Zanardi, Federico Pecora +2

Multi-Agent Path Finding is a fundamental problem in robotics and AI, yet most existing formulations treat planning and execution separately and address variants of the problem in…

cs.RO2025

Multi-Agent Path Finding via Finite-Horizon Hierarchical Factorization

Jiarui Li, Alessandro Zanardi, Gioele Zardini

We present a novel algorithm for large-scale Multi-Agent Path Finding (MAPF) that enables fast, scalable planning in dynamic environments such as automated warehouses. Our approach…