Study of Variational Inference for Flexible Distributed Probabilistic Robotics

Malte Rørmose Damgaard*, Rasmus Pedersen, Thomas Bak

*Kontaktforfatter

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

2 Citationer (Scopus)
57 Downloads (Pure)

Abstract

By combining stochastic variational inference with message passing algorithms, we show how to solve the highly complex problem of navigation and avoidance in distributed multi-robot systems in a computationally tractable manner, allowing online implementation. Subsequently, the proposed variational method lends itself to more flexible solutions than prior methodologies. Furthermore, the derived method is verified both through simulations with multiple mobile robots and a real world experiment with two mobile robots. In both cases, the robots share the operating space and need to cross each other’s paths multiple times without colliding.

OriginalsprogEngelsk
Artikelnummer38
TidsskriftRobotics
Vol/bind11
Udgave nummer2
ISSN2218-6581
DOI
StatusUdgivet - apr. 2022

Bibliografisk note

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© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

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