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Aerial infrastructures inspection
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-4383-7316
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
2023 (English)In: Aerial Robotic Workers: Design, Modeling, Control, Vision, and Their Applications / [ed] George Nikolakopoulos, Sina Sharif Mansouri, Christoforos Kanellakis, Elsevier, 2023, p. 175-211Chapter in book (Other academic)
Abstract [en]

This chapter presents the application of autonomous Aerial Robotic Workers towards performing a visual inspection of 3D infrastructures by utilizing single and multiple Aerial Robotic Workers (ARWs). To address this problem, the developed framework combines the fundamental tasks of path planning, localization, and mapping, which are the essential components for autonomous robotic navigation systems. In the presented approach, the Unmanned Aerial Workers (ARWs) deployed for inspecting the structure rely only on their onboard computer and sensory system. Initially, the problem of path planner is discussed and mathematically formulated, leading to the development of a geometry-based approach for coverage of complex structures. The navigation of the platform is performed through the localization component, which provides accurate pose estimation for the vehicle using a visual-inertial estimation scheme. During the coverage mission, the agents collect image data for post-processing and mapping using Visual SLAM and Structure from Motion techniques. The performance of the proposed framework has been experimentally evaluated in multiple indoor and realistic outdoor infrastructure inspection experiments, depicting the merits of the autonomous navigation system (path planning and localization) and 3D model building of the inspected object and infrastructure.

Place, publisher, year, edition, pages
Elsevier, 2023. p. 175-211
Keywords [en]
Infrastructure inspections, ARWs, Autonomy, Visual inspection, 3D point cloud
National Category
Control Engineering Robotics and automation
Research subject
Robotics and Artificial Intelligence
Identifiers
URN: urn:nbn:se:ltu:diva-97393DOI: 10.1016/B978-0-12-814909-6.00017-2Scopus ID: 2-s2.0-85150100105ISBN: 978-0-12-814909-6 (print)OAI: oai:DiVA.org:ltu-97393DiVA, id: diva2:1758923
Available from: 2023-05-24 Created: 2023-05-24 Last updated: 2025-10-21Bibliographically approved

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Kottayam Viswanathan, VigneshMansouri, Sina SharifKanellakis, Christoforos

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