Scalable Co-optimization of Collective Robotic Mobility and the Artificial Environment

Informazioni relative al progetto

gAIa

ID dell’accordo di sovvenzione: 949940

DOI

10.3030/949940

Data della firma CE 7 Ottobre 2020

Data di avvio 1 Gennaio 2021

Data di completamento 30 Giugno 2026

Finanziato da

• EXCELLENT SCIENCE - European Research Council (ERC)

Costo totale

€ 1 495 338,00

Contributo UE

€ 1 495 338,00

Coordinato da

THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
United Kingdom

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Pubblicazioni

Conference proceedings (12)

Environment Optimization for Multi-Agent Navigation

Autori: Zhan Gao, Amanda Prorok
Pubblicato in: International Conference on Robotics and Automation, 2023
Editore: IEEE
DOI: 10.48550/arxiv.2209.11279

Accelerating Multi-Agent Planning Using Graph Transformers with Bounded Suboptimality

Autori: Chenning Yu, Qingbiao Li, Sicun Gao, Amanda Prorok
Pubblicato in: International Conference on Robotics and Automation 2023, 2023
Editore: ICRA 2023
DOI: 10.48550/arxiv.2301.08451

Heterogeneous Multi-Robot Reinforcement Learning

Autori: Matteo Bettini, Ajay Shankar, Amanda Prorok
Pubblicato in: International Conference on Autonomous Agents and Multiagent Systems, 2023
Editore: AAMAS 2023

VMAS: A Vectorized Multi-Agent Simulator for Collective Robot Learning

Autori: Matteo Bettini, Ryan Kortvelesy, Jan Blumenkamp, Amanda Prorok
Pubblicato in: The 16th International Symposium on Distributed Autonomous Robotic Systems 2022, 2022
Editore: International Symposium on Distributed Autonomous Robotic Systems 2022

Modeling Partially Observable Systems using Graph-Based Memory and Topological Priors

Autori: Steven Morad, Stephan Liwicki, Ryan Kortvelesy, Roberto Mecca, Amanda Prorok
Pubblicato in: Learning for Dynamics and Control Conference (L4DC), 2022, Pagina/e 59-73
Editore: Proceedings of Machine Learning Research (PMLR)

A Framework for Real-World Multi-Robot Systems Running Decentralized GNN-Based Policies

Autori: Jan Blumenkamp; Steven Morad; Jennifer Gielis; Qingbiao Li; Amanda Prorok
Pubblicato in: IEEE International Conference on Robotics and Automation (ICRA), Numero 4, 2022, ISBN 978-1-7281-9681-7
Editore: IEEE International Conference on Robotics and Automation (ICRA)
DOI: 10.48550/arxiv.2111.01777

ModGNN: Expert Policy Approximation in Multi-Agent Systems with a Modular Graph Neural Network Architecture

Autori: Ryan Kortvelesy; Amanda Prorok
Pubblicato in: IEEE International Conference on Robotics and Automation (ICRA), Numero 1, 2021, ISBN 978-1-7281-9077-8
Editore: IEEE
DOI: 10.1109/icra48506.2021.9561386

The Holy Grail of Multi-Robot Planning: Learning to Generate Online-Scalable Solutions from Offline-Optimal Experts

Autori: Prorok, Amanda; Blumenkamp, Jan; Li, Qingbiao; Kortvelesy, Ryan; Liu, Zhe; Stump, Ethan
Pubblicato in: Autonomous Agents and Multi-Agent Systems (AAMAS), Numero 3, 2022, ISBN 978-1-4503-9213-6
Editore: IFFAAMAS
DOI: 10.48550/arxiv.2107.12254

Graph Neural Network Guided Local Search for the Traveling Salesperson Problem

Autori: Benjamin Hudson, Qingbiao Li, Matthew Malencia, Amanda Prorok
Pubblicato in: International Conference on Learning Representations (ICLR), 2022
Editore: International Conference on Learning Representations (ICLR)

Permutation-Invariant Set Autoencoders with Fixed-Size Embeddings for Multi-Agent Learning

Autori: Ryan Kortvelesy, Steven Morad, Amanda Prorok
Pubblicato in: International Conference on Autonomous Agents and Multiagent Systems, 2023
Editore: AAMAS
DOI: 10.48550/arxiv.2302.12826

See What the Robot Can’t See: Learning Cooperative Perception for Visual Navigation

Autori: Jan Blumenkamp, Qingbiao Li, Binyu Wang, Zhe Liu, Amanda Prorok
Pubblicato in: International Conference on Intelligent Robots and Systems, 2023
Editore: IEEE

Graph Convolutional Memory using Topological Priors

Autori: Steven Morad, Stephan Liwicki, Ryan Kortvelesy, Roberto Mecca, Amanda Prorok
Pubblicato in: Learning for Dynamics & Control Conference 2022, 2022
Editore: Learning for Dynamics & Control Conference
DOI: 10.48550/arXiv.2106.14117

Peer reviewed articles (4)

Message-Aware Graph Attention Networks for Large-Scale Multi-Robot Path Planning

Autori: Qingbiao Li, Weizhe Lin, Zhe Liu, Amanda Prorok
Pubblicato in: IEEE Robotics and Automation Letters (R-AL), 2021, 2021, Pagina/e 5533 - 5540, ISSN 2377-3766
Editore: IEEE

A Critical Review of Communications in Multi‑robot Systems

Autori: Jennifer Gielis, Ajay Shankar, Amanda Prorok
Pubblicato in: Current Robotics Reports, 2022, Pagina/e 000-000000, ISSN 0000-0000
Editore: Springer
DOI: 10.1007/s43154-022-00090-9

Constrained Environment Optimization for Prioritized Multi-Agent Navigation

Autori: Zhan Gao and Amanda Prorok
Pubblicato in: IEEE Open Journal of Control Systems (OJ-CSYS), 2023, ISSN 2694-085X
Editore: IEEE

Explanation-Aware Experience Replay in Rule-Dense Environments

Autori: Francesco Sovrano; Alex Raymond; Amanda Prorok
Pubblicato in: IEEE Robotics and Automation Letters, Numero 3, 2021, ISSN 2377-3766
Editore: IEEE
DOI: 10.1109/lra.2021.3135927