Aerial navigation in obstructed environments with embedded nonlinear model predictive controlShow others and affiliations
2019 (English)In: 2019 18th European Control Conference (ECC), IEEE, 2019, p. 3556-3563Conference paper, Published paper (Refereed)
Abstract [en]
We propose a methodology for autonomous aerial navigation and obstacle avoidance of micro aerial vehicles (MAVs) using non-linear model predictive control (NMPC) and we demonstrate its effectiveness with laboratory experiments. The proposed methodology can accommodate obstacles of arbitrary, potentially non-convex, geometry. The NMPC problem is solved using PANOC: a fast numerical optimization method which is completely matrix-free, is not sensitive to ill conditioning, involves only simple algebraic operations and is suitable for embedded NMPC. A c89 implementation of PANOC solves the NMPC problem at a rate of 20 Hz on board a lab-scale MAV. The MAV performs smooth maneuvers moving around an obstacle. For increased autonomy, we propose a simple method to compensate for the reduction of thrust over time, which comes from the depletion of the MAV's battery, by estimating the thrust constant.
Place, publisher, year, edition, pages
IEEE, 2019. p. 3556-3563
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-85981DOI: 10.23919/ECC.2019.8796236ISI: 000490488303095Scopus ID: 2-s2.0-85071583638OAI: oai:DiVA.org:ltu-85981DiVA, id: diva2:1573122
Conference
18th European Control Conference (ECC 2019), Naples, Italy, June 25-28, 2019
Funder
EU, Horizon 2020, 730302, 739551
Note
ISBN för värdpublikation: 978-3-907144-00-8;
Finansiär: FWO projects (G086318N, G086518N); Fonds de la Recherche Scientifique — FNRS; Fonds Wetenschappelijk Onderzoek — Vlaanderen (30468160); Research Council KU Leuven (C14/18/068)
2021-06-242021-06-242024-03-07Bibliographically approved