A review of artificial intelligence applied to path planning in UAV swarms

A Puente-Castro, D Rivero, A Pazos… - Neural Computing and …, 2022 - Springer
Abstract Path Planning problems with Unmanned Aerial Vehicles (UAVs) are among the
most studied knowledge areas in the related literature. However, few of them have been …

Graph neural networks in IoT: A survey

G Dong, M Tang, Z Wang, J Gao, S Guo, L Cai… - ACM Transactions on …, 2023 - dl.acm.org
The Internet of Things (IoT) boom has revolutionized almost every corner of people's daily
lives: healthcare, environment, transportation, manufacturing, supply chain, and so on. With …

Graph neural networks for decentralized multi-robot path planning

Q Li, F Gama, A Ribeiro, A Prorok - 2020 IEEE/RSJ international …, 2020 - ieeexplore.ieee.org
Effective communication is key to successful, decentralized, multi-robot path planning. Yet, it
is far from obvious what information is crucial to the task at hand, and how and when it must …

A critical review of communications in multi-robot systems

J Gielis, A Shankar, A Prorok - Current robotics reports, 2022 - Springer
Abstract Purpose of Review This review summarizes the broad roles that communication
formats and technologies have played in enabling multi-robot systems. We approach this …

Stability properties of graph neural networks

F Gama, J Bruna, A Ribeiro - IEEE Transactions on Signal …, 2020 - ieeexplore.ieee.org
Graph neural networks (GNNs) have emerged as a powerful tool for nonlinear processing of
graph signals, exhibiting success in recommender systems, power outage prediction, and …

Graphs, convolutions, and neural networks: From graph filters to graph neural networks

F Gama, E Isufi, G Leus… - IEEE Signal Processing …, 2020 - ieeexplore.ieee.org
Network data can be conveniently modeled as a graph signal, where data values are
assigned to nodes of a graph that describes the underlying network topology. Successful …

Message-aware graph attention networks for large-scale multi-robot path planning

Q Li, W Lin, Z Liu, A Prorok - IEEE Robotics and Automation …, 2021 - ieeexplore.ieee.org
The domains of transport and logistics are increasingly relying on autonomous mobile
robots for the handling and distribution of passengers or resources. At large system scales …

Gated graph recurrent neural networks

L Ruiz, F Gama, A Ribeiro - IEEE Transactions on Signal …, 2020 - ieeexplore.ieee.org
Graph processes exhibit a temporal structure determined by the sequence index and and a
spatial structure determined by the graph support. To learn from graph processes, an …

Human-robot teaming: grand challenges

M Natarajan, E Seraj, B Altundas, R Paleja, S Ye… - Current Robotics …, 2023 - Springer
Abstract Purpose of Review Current real-world interaction between humans and robots is
extremely limited. We present challenges that, if addressed, will enable humans and robots …

Optimal power flow using graph neural networks

D Owerko, F Gama, A Ribeiro - ICASSP 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
Optimal power flow (OPF) is one of the most important optimization problems in the energy
industry. In its simplest form, OPF attempts to find the optimal power that the generators …