Imperial College London
Alternate

ProfessorAndrewDavison

Faculty of Engineering, Department of Computing

Professor of Robot Vision
 
 
 
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Contact

 

+44 (0)20 7594 8316a.davison Website

 
 
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Assistant

 

Ms Lucy Atthis +44 (0)20 7594 8259

 
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Location

 

303William Penney LaboratorySouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Patwardhan:2023:10.1109/LRA.2022.3227858,
author = {Patwardhan, A and Murai, R and Davison, AJ},
doi = {10.1109/LRA.2022.3227858},
journal = {IEEE Robotics and Automation Letters},
pages = {552--559},
title = {Distributing collaborative multi-robot planning with Gaussian belief propagation},
url = {http://dx.doi.org/10.1109/LRA.2022.3227858},
volume = {8},
year = {2023}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Precise coordinated planning over a forward time window enables safe and highly efficient motion when many robots must work together in tight spaces, but this would normally require centralised control of all devices which is difficult to scale. We demonstrate GBP Planning, a new purely distributed technique based on Gaussian Belief Propagation for multi-robot planning problems, formulated by a generic factor graph defining dynamics and collision constraints over a forward time window. In simulations, we show that our method allows high performance collaborative planning where robots are able to cross each other in busy, intricate scenarios. They maintain shorter, quicker and smoother trajectories than alternative distributed planning techniques even in cases of communication failure. We encourage the reader to view the accompanying video demonstration.
AU  - Patwardhan,A
AU  - Murai,R
AU  - Davison,AJ
DO  - 10.1109/LRA.2022.3227858
EP  - 559
PY  - 2023///
SN  - 2377-3766
SP  - 552
TI  - Distributing collaborative multi-robot planning with Gaussian belief propagation
T2  - IEEE Robotics and Automation Letters
UR  - http://dx.doi.org/10.1109/LRA.2022.3227858
UR  - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000902032700005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
UR  - https://ieeexplore.ieee.org/document/9976221
VL  - 8
ER  -
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