☆ 4.6 Article

Hierarchical Planning for Heterogeneous Multi-Robot Routing Problems via Learned Subteam Performance

IEEE ROBOTICS AND AUTOMATION LETTERS (2022)

A Comprehensive Survey on Graph Neural Networks

Zonghan Wu et al.

Summary: This article provides a comprehensive overview of graph neural networks (GNNs) in data mining and machine learning fields. It discusses the taxonomy of GNNs, their applications, and summarizes open-source codes, benchmark data sets, and model evaluation. The article also proposes potential research directions in this rapidly growing field.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)

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Article Computer Science, Information Systems

Spatially-Distributed Missions With Heterogeneous Multi-Robot Teams

Eduardo Feo-Flushing et al.

Summary: This work focuses on mission planning in teams of mobile autonomous agents, aiming to assign tasks to agents to maximize mission performance. The mission planning problem is approached through a model that includes task selection and allocation, task scheduling, task routing, and control of agent proximity over time, formalized as a mixed integer linear program (MILP). Two solution approaches, heuristic and exact methods, are proposed to tackle the NP-hard problem, resulting in efficient anytime algorithms.

IEEE ACCESS (2021)

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Article Robotics