6 papers
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…
Compositional Online Learning for Multi-Objective System Co-Design
Meshal Alharbi, Munther A. Dahleh, Gioele Zardini
Many engineered systems must balance competing objectives, such as performance and safety, cost and reliability, or efficiency and sustainability, and are naturally modeled as comp…
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…
Scalable Co-Design via Linear Design Problems: Compositional Theory and Algorithms
Yubo Cai, Yujun Huang, Meshal Alharbi +1
Designing complex engineered systems requires managing tightly coupled trade-offs between subsystem capabilities and resource requirements. Monotone co-design provides a compositio…
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…
Reproducibility in the Control of Autonomous Mobility-on-Demand Systems
Xinling Li, Meshal Alharbi, Daniele Gammelli +7
Autonomous Mobility-on-Demand (AMoD) systems, powered by advances in robotics, control, and Machine Learning (ML), offer a promising paradigm for future urban transportation. AMoD…