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      Inspection of Pole-Like Structures Using a Visual-Inertial Aided VTOL Platform with Shared Autonomy

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          Abstract

          This paper presents an algorithm and a system for vertical infrastructure inspection using a vertical take-off and landing (VTOL) unmanned aerial vehicle and shared autonomy. Inspecting vertical structures such as light and power distribution poles is a difficult task that is time-consuming, dangerous and expensive. Recently, micro VTOL platforms ( i.e., quad-, hexa- and octa-rotors) have been rapidly gaining interest in research, military and even public domains. The unmanned, low-cost and VTOL properties of these platforms make them ideal for situations where inspection would otherwise be time-consuming and/or hazardous to humans. There are, however, challenges involved with developing such an inspection system, for example flying in close proximity to a target while maintaining a fixed stand-off distance from it, being immune to wind gusts and exchanging useful information with the remote user. To overcome these challenges, we require accurate and high-update rate state estimation and high performance controllers to be implemented onboard the vehicle. Ease of control and a live video feed are required for the human operator. We demonstrate a VTOL platform that can operate at close-quarters, whilst maintaining a safe stand-off distance and rejecting environmental disturbances. Two approaches are presented: Position-Based Visual Servoing (PBVS) using an Extended Kalman Filter (EKF) and estimator-free Image-Based Visual Servoing (IBVS). Both use monocular visual, inertia, and sonar data, allowing the approaches to be applied for indoor or GPS-impaired environments. We extensively compare the performances of PBVS and IBVS in terms of accuracy, robustness and computational costs. Results from simulations and indoor/outdoor (day and night) flight experiments demonstrate the system is able to successfully inspect and circumnavigate a vertical pole.

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          Visual servo control. I. Basic approaches

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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                02 September 2015
                September 2015
                : 15
                : 9
                : 22003-22048
                Affiliations
                [1 ]Science and Engineering Faculty, Queensland University of Technology, Brisbane 4000, Australia; E-Mail: peter.corke@ 123456qut.edu.au
                [2 ]CSIRO Digital Productivity, Brisbane 4069, Australia; E-Mail: Stefan.Hrabar@ 123456csiro.au
                Author notes
                [* ]Author to whom correspondence should be addressed; E-Mail: i.sa@ 123456qut.edu.au ; Tel.: +61-449-722-415; Fax: +61-7-3138-8822.
                Article
                sensors-15-22003
                10.3390/s150922003
                4610434
                26340631
                e8f36f70-ce5f-4764-8190-dd72d8f0a802
                © 2015 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 14 July 2015
                : 26 August 2015
                Categories
                Article

                Biomedical engineering
                aerial robotics,pole inspection,visual servoing, shared autonomy
                Biomedical engineering
                aerial robotics, pole inspection, visual servoing, shared autonomy

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