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Networked operation of a UAV using Gaussian process-based delay compensation and model predictive control
SNU, Dept Mech & Aerosp Engn, Seoul, South Korea.;ASRI, Seoul, South Korea..
Hankyong Natl Univ, Dept Elect Elect & Control Engn, Anseong, South Korea..
SNU, Dept Mech & Aerosp Engn, Seoul, South Korea.;ASRI, Seoul, South Korea..
SNU, Dept Mech & Aerosp Engn, Seoul, South Korea.;ASRI, Seoul, South Korea..
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2019 (English)In: 2019 International Conference on Robotics And Automation (ICRA) / [ed] Howard, A Althoefer, K Arai, F Arrichiello, F Caputo, B Castellanos, J Hauser, K Isler, V Kim, J Liu, H Oh, P Santos, V Scaramuzza, D Ude, A Voyles, R Yamane, K Okamura, A, Institute of Electrical and Electronics Engineers (IEEE), 2019, Vol. 2019, p. 9216-9222Conference paper, Published paper (Refereed)
Abstract [en]

This study addresses an operation of unmanned aerial vehicles (UAVs) in a network environment where there is time-varying network delay. The network delay entails undesirable effects on the stability of the UAV control system due to delayed state feedback and outdated control input. Although several networked control algorithms have been proposed to deal with the network delay, most existing studies have assumed that the plant dynamics is known and simple, or the network delay is constant. These assumptions are improper to multirotor-type UAVs because of their nonlinearity and time-sensitive characteristics. To deal with these problems, we propose a networked control system using model predictive control (MPC) designed under the consideration of multirotor characteristics. We also apply a Gaussian process (GP) to learn an unknown nonlinear model, which increases the accuracy of path planning and state estimation. Flight experiments show that the proposed algorithm successfully compensates the network delay and Gaussian process learning improves the UAV's path tracking performance.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019. Vol. 2019, p. 9216-9222
Series
IEEE International Conference on Robotics and Automation ICRA, ISSN 1050-4729
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-265473DOI: 10.1109/ICRA.2019.8793472ISI: 000494942306111Scopus ID: 2-s2.0-85071493357ISBN: 978-1-5386-6026-3 (print)OAI: oai:DiVA.org:kth-265473DiVA, id: diva2:1380004
Conference
2019 International Conference on Robotics and Automation, ICRA 2019; Palais des Congres de Montreal, Montreal; Canada; 20 May 2019 through 24 May 2019
Available from: 2019-12-18 Created: 2019-12-18 Last updated: 2019-12-19Bibliographically approved

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Johansson, Karl H.

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