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Clark, R.A.; Punzo, G.; MacLeod, C.N.; Dobie, G.; Summan, R.; Bolton, G.; Pierce, S.G.; Macdonald, M. (2017)
Publisher: Elsevier
Languages: English
Types: Article
Subjects:
© 2016 Elsevier B.V.A novel approach to the autonomous generation of trajectories for multiple aerial vehicles is presented, whereby an artificial kinematic field provides autonomous control in a distributed and highly scalable manner. The kinematic field is generated relative to a central target and is modified when a vehicle is in close proximity of another to avoid collisions. This control scheme is then applied to the mock visual inspection of a nuclear intermediate level waste storage drum. The inspection is completed using two commercially available quadcopters, in a laboratory environment, with the acquired visual inspection data processed and photogrammetrically meshed to generate a three-dimensional surface-meshed model of the drum. This paper contributes to the field of multi-agent coverage path planning for structural inspection and provides experimental validation of the control and inspection results.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [2] S. Esposito, P. Fallavollita, W. Wahbeh, C. Nardinocchi, M. Balsi, Performance evaluation of UAV photogrammetric 3D reconstruction., in: IGARSS, 4788-4791, 2014.
    • [3] F. Bonnin-Pascual, E. Garcia-Fidalgo, A. Ortiz, Semi-autonomous visual inspection of vessels assisted by an unmanned micro aerial vehicle, in: Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on, IEEE, 3955-3961, 2012.
    • [4] J. Nikolic, M. Burri, J. Rehder, S. Leutenegger, C. Huerzeler, R. Siegwart, A UAV system for inspection of industrial facilities, in: Aerospace Conference, 2013 IEEE, IEEE, 1-8, 2013.
    • [5] M. Burri, J. Nikolic, C. Hurzeler, G. Caprari, R. Siegwart, Aerial service robots for visual inspection of thermal power plant boiler systems, in: Applied Robotics for the Power Industry (CARPI), 2012 2nd International Conference on, IEEE, 70-75, 2012.
    • [6] A. Ortiz, F. Bonnin-Pascual, E. Garcia-Fidalgo, Vessel Inspection: A Micro-Aerial Vehicle-based Approach, Journal of Intelligent & Robotic Systems 76 (1) (2014) 151-167.
    • [7] R. Khanna, M. Moller, J. Pfeifer, F. Liebisch, A. Walter, R. Siegwart, Beyond point clouds-3D mapping and field parameter measurements using UAVs, in: Emerging Technologies & Factory Automation (ETFA), 2015 IEEE 20th Conference on, IEEE, 1-4, 2015.
    • [8] F. Remondino, L. Barazzetti, F. Nex, M. Scaioni, D. Sarazzi, UAV photogrammetry for mapping and 3d modeling-current status and future perspectives, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 38 (1) (2011) C22.
    • [9] J. Liu, H. Wang, X. Liu, F. Li, G. Sun, P. Song, An automated 3D reconstruction method of UAV images, in: Applied Optics and Photonics China (AOPC2015), International Society for Optics and Photonics, 96780S-96780S, 2015.
    • [10] J. S. Bellingham, M. Tillerson, M. Alighanbari, J. P. How, Cooperative path planning for multiple UAVs in dynamic and uncertain environments, in: Decision and Control, 2002, Proceedings of the 41st IEEE Conference on, vol. 3, IEEE, 2816-2822, 2002.
    • [11] M. Shanmugavel, A. Tsourdos, B. White, R. Z˙bikowski, Co-operative path planning of multiple UAVs using Dubins paths with clothoid arcs, Control Engineering Practice 18 (9) (2010) 1084-1092.
    • [12] E. Galceran, M. Carreras, A survey on coverage path planning for robotics, Robotics and Autonomous Systems 61 (12) (2013) 1258-1276.
    • [13] L. Babel, Flight path planning for unmanned aerial vehicles with landmark-based visual navigation, Robotics and Autonomous Systems 62 (2) (2014) 142-150.
    • [14] A. Barrientos, J. Colorado, J. d. Cerro, A. Martinez, C. Rossi, D. Sanz, J. Valente, Aerial remote sensing in agriculture: A practical approach to area coverage and path planning for fleets of mini aerial robots, Journal of Field Robotics 28 (5) (2011) 667-689.
    • [15] G. Murtaza, S. Kanhere, S. Jha, Priority-based coverage path planning for aerial wireless sensor networks, in: Intelligent Sensors, Sensor Networks and Information Processing, 2013 IEEE Eighth International Conference on, IEEE, 219-224, 2013.
    • [16] O. Khatib, Real-time obstacle avoidance for manipulators and mobile robots, The international journal of robotics research 5 (1) (1986) 90-98.
    • [17] D. F. Gordon, W. M. Spears, O. Sokolsky, I. Lee, Distributed spatial control, global monitoring and steering of mobile agents, in: Information Intelligence and Systems, 1999. Proceedings. 1999 International Conference on, IEEE, 681-688, 1999.
    • [18] W. M. Spears, D. F. Gordon, Using artificial physics to control agents, in: Information Intelligence and Systems, 1999. Proceedings. 1999 International Conference on, IEEE, 281-288, 1999.
    • [19] N. E. Leonard, E. Fiorelli, Virtual leaders, artificial potentials and coordinated control of groups, in: Decision and Control, 2001. Proceedings of the 40th IEEE Conference on, vol. 3, IEEE, 2968-2973, 2001.
    • [20] N. E. Leonard, D. A. Paley, F. Lekien, R. Sepulchre, D. M. Fratantoni, R. E. Davis, Collective motion, sensor networks, and ocean sampling, Proceedings of the IEEE 95 (1) (2007) 48-74.
    • [21] D. A. Lawrence, E. W. Frew, W. J. Pisano, Lyapunov vector fields for autonomous unmanned aircraft flight control, Journal of Guidance, Control, and Dynamics 31 (5) (2008) 1220-1229.
    • [22] E. W. Frew, D. A. Lawrence, S. Morris, Coordinated standoff tracking of moving targets using Lyapunov guidance vector fields, Journal of guidance, control, and dynamics 31 (2) (2008) 290-306.
    • [23] D. J. Bennet, C. McInnes, Verifiable control of a swarm of unmanned aerial vehicles, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 223 (7) (2009) 939-953.
    • [24] S. B. McCamish, M. Romano, X. Yun, Autonomous distributed control of simultaneous multiple spacecraft proximity maneuvers, Automation Science and Engineering, IEEE Transactions on 7 (3) (2010) 630-644.
    • [25] C. Vasile, A. Pavel, C. Buiu, Integrating human swarm interaction in a distributed robotic control system, in: Automation Science and Engineering (CASE), 2011 IEEE Conference on, IEEE, 743-748, 2011.
    • [26] C. Harris, M. Stephens, A combined corner and edge detector., in: Alvey vision conference, vol. 15, Citeseer, 50, 1988.
    • [27] P. Hansen, H. Alismail, P. Rander, B. Browning, Pipe mapping with monocular fisheye imagery, in: Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on, IEEE, 5180-5185, 2013.
    • [28] S. El Kahi, D. Asmar, A. Fakih, J. Nieto, E. Nebot, A vison-based system for mapping the inside of a pipe, in: Robotics and Biomimetics (ROBIO), 2011 IEEE International Conference on, IEEE, 2605-2611, 2011.
    • [29] J. Shi, C. Tomasi, Good features to track, in: Computer Vision and Pattern Recognition, 1994. Proceedings CVPR'94., 1994 IEEE Computer Society Conference on, IEEE, 593-600, 1994.
    • [30] G. Dobie, R. Summan, C. MacLeod, S. G. Pierce, Visual odometry and image mosaicing for NDE, NDT & E International 57 (2013) 17-25.
    • [31] M. L. Brutto, P. Meli, Computer vision tools for 3D modelling in archaeology, International Journal of Heritage in the Digital Era 1 (1 suppl) (2012) 1-6.
    • [32] T. P. Kersten, M. Lindstaedt, Image-based low-cost systems for automatic 3D recording and modelling of archaeological finds and objects, in: Progress in cultural heritage preservation, Springer, 1-10, 2012.
    • [33] Vicon, Vicon motion tracking system, http://www.vicon.com/ Software/Tracker, [Online; accessed January-2015], 2015.
    • [34] Parrot, Parrot AR.Drone 2.0 Technical Specifications, http:// ardrone2.parrot.com/ardrone-2/specifications//, [Online; accessed January-2015], 2015.
    • [35] Nikon, Nikon D3200, http://www.europe-nikon.com/en\_GB/ product/digital-cameras/slr/consumer/d3200/, [Online; accessed January-2015], 2015.
    • [36] AF-S DX NIKKOR 18-55mm f/3.5-5.6G http://www.europe-nikon.com/en\_GB/product/ nikkor-lenses/auto-focus-lenses/dx/zoom/ af-s-dx-nikkor-18-55mm-f-3-5-5-6g-vr, [Online; January-2015], 2015.
    • [38] P. Misra, P. Enge, Global Positioning System: Signals, Measurements and Performance Second Edition, Lincoln, MA: Ganga-Jamuna Press, 2006.
    • [39] Autodesk, Autodesk 123D Catch, http://www.123dapp.com/catch, [Online; accessed February-2015], 2015.
    • [40] P. Azad, T. Gockel, R. Dillmann, Computer Vision: principles and practice .
    • [41] Autodesk, Calibration toolbox, http://www.123dapp.com/catch, [Online; accessed February-2015], 2015.
    • [42] Geomagic Control, http://www.geomagic.com/en/products/ qualify/overview, [Online; accessed January-2015], 2015.
    • [43] J. Kelly, G. S. Sukhatme, Visual-inertial sensor fusion: Localization, mapping and sensor-to-sensor self-calibration, The International Journal of Robotics Research 30 (1) (2011) 56-79.
    • [44] J. Engel, T. Scho¨ps, D. Cremers, LSD-SLAM: Large-scale direct monocular SLAM, in: Computer Vision-ECCV 2014, Springer, 834-849, 2014.
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