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On vision enabled aerial manipulation for multirotors
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-2001-7171
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-0126-1897
2018 (English)In: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2018Conference paper, Published paper (Refereed)
Abstract [en]

This article presents an integrated vision-based guiding system for aerial manipulation. More specifically, a 4 DoF planar dexterous manipulator, with a stereo camera attached on the end-effector, is endowed to a multirotor aerial platform enabling active manipulation capabilities. The proposed novel approach combines a visual processing scheme for object detection and tracking, as well as a manipulator positioning for allowing the aerial platform to approach the surface of interaction efficiently. In the developed scheme, the object detection is based on correlation filters to track the target robustly, while the depth information, from the stereo camera on board the manipulator, is used to extract the centroid of the manipulated object, compute its relative configuration with respect to the UAV and align the end-effector properly with the grasping point. The effectiveness of the proposed scheme is demonstrated in multiple experimental trials and simulations, highlighting it's applicability towards autonomous aerial manipulation.

Place, publisher, year, edition, pages
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2018.
Series
IEEE International Conference on Emerging Technologies and Factory Automation, ISSN 1946-0759
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-67631DOI: 10.1109/ETFA.2017.8247653Scopus ID: 2-s2.0-85044436802ISBN: 978-1-5090-6505-9 (electronic)ISBN: 978-1-5090-6506-6 (print)OAI: oai:DiVA.org:ltu-67631DiVA, id: diva2:1182500
Conference
22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Limassol, Cyprus, September 12-15, 2017
Projects
Collaborative Aerial Robotic Workers, AEROWORKS
Funder
EU, Horizon 2020, 644128Available from: 2018-02-13 Created: 2018-02-13 Last updated: 2018-05-29Bibliographically approved

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Kanellakis, ChristoforosTerreran, MatteoKominiak, DariuszNikolakopoulos, George
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