5 papers · 1 filter
Graph Learning-based Fleet Scheduling for Urban Air Mobility under Operational Constraints, Varying Demand & Uncertainties
Steve Paul, Jhoel Witter, Souma Chowdhury
This paper develops a graph reinforcement learning approach to online planning of the schedule and destinations of electric aircraft that comprise an urban air mobility (UAM) fleet…
Fast Decision Support for Air Traffic Management at Urban Air Mobility Vertiports using Graph Learning
Prajit KrisshnaKumar, Jhoel Witter, Steve Paul +3
Urban Air Mobility (UAM) promises a new dimension to decongested, safe, and fast travel in urban and suburban hubs. These UAM aircraft are conceived to operate from small airports…
Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction
Steve Paul, Wenyuan Li, Brian Smyth +3
Efficient multi-robot task allocation (MRTA) is fundamental to various time-sensitive applications such as disaster response, warehouse operations, and construction. This paper tac…
Graph Learning Based Decision Support for Multi-Aircraft Take-Off and Landing at Urban Air Mobility Vertiports
Prajit KrisshnaKumar, Jhoel Witter, Steve Paul +2
Majority of aircraft under the Urban Air Mobility (UAM) concept are expected to be of the electric vertical takeoff and landing (eVTOL) vehicle type, which will operate out of vert…
Learning Scalable Policies over Graphs for Multi-Robot Task Allocation using Capsule Attention Networks
Steve Paul, Payam Ghassemi, Souma Chowdhury
This paper presents a novel graph reinforcement learning (RL) architecture to solve multi-robot task allocation (MRTA) problems that involve tasks with deadlines and workload, and…