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Subterranean MAV Navigation based on Nonlinear MPC with Collision Avoidance Constraints
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-7631-002x
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-8870-6718
WideFind AB, Aurorum 1C, Luleå SE-97775, Sweden.ORCID iD: 0000-0001-5735-5484
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-3922-1735
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2020 (English)In: 21th IFAC World Congress / [ed] Rolf Findeisen, Sandra Hirche, Klaus Janschek, Martin Mönnigmann, Elsevier, 2020, p. 9650-9657Conference paper, Published paper (Refereed)
Abstract [en]

Micro Aerial Vehicles (MAVs) navigation in subterranean environments is gaining attention in the field of aerial robotics, however there are still multiple challenges for collision free navigation in such harsh environments. This article proposes a novel baseline solution for collision free navigation with Nonlinear Model Predictive Control (NMPC). In the proposed method, the MAV is considered as a floating object, where the velocities on the x, y axes and the position on altitude are the references for the NMPC to navigate along the tunnel, while the NMPC avoids the collision by considering kinematics of the obstacles based on measurements from a 2D lidar. Moreover, a novel approach for correcting the heading of the MAV towards the center of the mine tunnel is proposed, while the efficacy of the suggested framework has been evaluated in multiple field trials in an underground mine in Sweden.

Place, publisher, year, edition, pages
Elsevier, 2020. p. 9650-9657
Series
IFAC-PapersOnLine, E-ISSN 2405-8963 ; 53 (2)
Keywords [en]
NMPC, Collision Avoidance, Subterranean, MAV, Autonomous Tunnel Inspection, Mining Aerial Robotics
National Category
Robotics
Research subject
Robotics and Artificial Intelligence; Automatic Control
Identifiers
URN: urn:nbn:se:ltu:diva-79114DOI: 10.1016/j.ifacol.2020.12.2612ISI: 000652593100140Scopus ID: 2-s2.0-85089911738OAI: oai:DiVA.org:ltu-79114DiVA, id: diva2:1433852
Conference
21st IFAC World Congress, Berlin, Germany, July 11-17, 2020
Funder
EU, Horizon 2020, 730302 SIMSAvailable from: 2020-06-01 Created: 2020-06-01 Last updated: 2021-12-13Bibliographically approved

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Mansouri, Sina SharifKanellakis, ChristoforosFresk, EmilLindqvist, BjörnKominiak, DariuszKoval, AntonNikolakopoulos, George

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