1 citations · 1 across the 6 of their papers we have counts for
8 papers
Auditable and Deployable Multi-Agent Motion Planning via Posetal Games from Legal Guidelines
Florian Lercher, Karan Mahesh, Yujun Huang +6
When robots are deployed in the real-world, they must interact with other agents and accomplish their own goals while adhering to legal constraints. These potentially conflicting o…
Compositional Sensitivity Analysis for Multiobjective System Co-Design
Alan Bonomi, Antonio Terpin, Yubo Cai +3
Sensitivity analysis of coupled systems typically propagates derivatives of single-valued maps, whereas multiobjective optimization generally treats sensitivity at the system level…
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
The design of multi-agent robotic systems involves tightly coupled decisions spanning heterogeneous domains, including robot design, fleet composition, and planning. Much effort ha…
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…