11 citations · 30 across the 47 of their papers we have counts for
14 papers · 1 filter
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…
Principles of Robot Autonomy
Daniele Gammelli, Joseph Lorenzetti, Katie Luo +2
Autonomous robots are moving rapidly from research labs into everyday life - on roads, in the air, in warehouses, and in space. Robot autonomy is no longer solely an academic pursu…
Task-Driven Co-Design of Heterogeneous Multi-Robot Systems
Maximilian Stralz, Meshal Alharbi, Yujun Huang +1
Designing multi-agent robotic systems requires reasoning across tightly coupled decisions spanning heterogeneous domains, including robot design, fleet composition, and planning. M…
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…
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…
GRAND: Guidance, Rebalancing, and Assignment for Networked Dispatch in Multi-Agent Path Finding
Johannes Gaber, Meshal Alharbi, Daniele Gammelli +1
Large robot fleets are now common in warehouses and other logistics settings, where small control gains translate into large operational impacts. In this article, we address task s…