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Navigation for Inspection

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Synonyms

Complete coverage of an AOI; Localization and mapping (for inspection); Motion and path planning (for inspection); Survey of an Area of Interest (AOI)

Definition

Navigation for inspection refers to both the hardware and software required to make a robotic platform undertake the different tasks involved in an inspection mission. This typically requires from the robot a number of capabilities at the locomotion, sensory, and “intelligence” levels which make it possible to collect inspection data of relevance, in accordance to the inspection procedures of application, while adequately covering the area of interest (AOI).

Overview

Installations and facilities such as industrial plants (e.g., from the power or petrochemical sectors), large-tonnage vessels, storage tanks, buildings, roads, bridges, tunnels, etc., to name but a few, deteriorate due to environmental factors or simply wear and tear. Therefore, the periodic maintenance of these facilities, including visual inspection of...

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References

  • Acar EU, Choset H, Rizzi AA, Atkar PN, Hull D (2002) Morse decompositions for coverage tasks. Int J Robot Res 21(4):331–344

    Article  Google Scholar 

  • Alarifi A, Al-Salman A, Alsaleh M, Alnafessah A, Al-Hadhrami S, Al-Ammar M, Al-Khalifa H (2016) Ultra wideband indoor positioning technologies: analysis and recent advances. Sensors 16(5):707

    Article  Google Scholar 

  • Antich J, Ortiz A (2008) A convergent dynamic window approach with minimal computational requirements. In: Proceedings of international conference on intelligent autonomous systems, pp 183–192

    Google Scholar 

  • Antich J, Ortiz A (2010) A rapid anytime path planner with incorporated range sensing to improve control on solution quality. In: Proceedings of the international conference on intelligent autonomous systems, pp 207–216

    Google Scholar 

  • Arkin R (1998) Behavior-based robotics. The MIT Press, Cambridge

    Google Scholar 

  • Bahr A, Feldman A, Colli-Vignarelli J, Robert S, Dehollain C, Martinoli A (2012) Modeling and benchmarking ultra-wideband localization for mobile robots. In: Proceedings of the IEEE international conference on Ultra-Wideband, pp 443–447. IEEE

    Google Scholar 

  • Bailey T, Durrant-Whyte H (2006) Simultaneous localization and mapping (slam): part II. IEEE Robot Autom Mag 13(3):108–117

    Article  Google Scholar 

  • Beevers KR, Huang WH (2006) Slam with sparse sensing. In: Proceedings of the IEEE international conference on robotics and automation, pp 2285–2290

    Google Scholar 

  • Beul M, Krombach N, Zhong Y, Droeschel D, Nieuwenhuisen M, Behnke S (2015) A high-performance mav for autonomous navigation in complex 3D environments. In: Proceedings of the IEEE international conference on unmanned aircraft systems, pp 1241–1250

    Google Scholar 

  • Blanco JL, Bellone M, Gimenez-Fernandez A (2015) TP-Space RRT: kinematic path planning of non-holonomic any-shape vehicles. Int J Adv Robot Syst 12(5):55

    Article  Google Scholar 

  • Bonnin-Pascual F, Ortiz A (2016) A flying tool for sensing vessel structure defects using image contrast-based saliency. IEEE Sensors J 16(15):6114–6121

    Article  Google Scholar 

  • Bordalba R, Porta J, Ros L (2017) Kinodynamic planning on constraint manifolds. Technical report, Kinematics and Robot Design Research Group, Institut de Robòtica i Informàtica Industrial, CSIC-UPC

    Google Scholar 

  • Cadena C, Carlone L, Carrillo H, Latif Y, Scaramuzza D, Neira J, Reid I, Leonard JJ (2016) Past, present, and future of simultaneous localization and mapping: toward the robust-perception age. IEEE Trans Robot 32(6):1309–1332

    Article  Google Scholar 

  • Chowdhary G, Johnson EN, Magree D, Wu A, Shein A (2013) GPS-denied indoor and outdoor monocular vision aided navigation and control of unmanned aircraft. J Field Rob 30(3):415–438

    Article  Google Scholar 

  • Cox IJ, Wilfong GT (eds) (1990) Autonomous robot vehicles. Springer, New York

    Google Scholar 

  • Cruz NA, Matos AC, Almeida RM, Ferreira BM, Abreu N (2011) TriMARES – a hybrid AUV/ROV for dam inspection. In: Proceedings of the IEEE/MTS OCEANS conference, pp 1–7

    Google Scholar 

  • Droeschel D, Schwarz M, Behnke S (2017) Continuous mapping and localization for autonomous navigation in rough terrain using a 3D laser scanner. Robot Auton Syst 88:104–115

    Article  Google Scholar 

  • Elbanhawi M, Simic M (2014) Sampling-based robot motion planning: a review. IEEE Acc 2:56–77

    Article  Google Scholar 

  • Englot B, Hover F (2012) Sampling-based coverage path planning for inspection of complex structures. In: Proceesings of the international conference on automated planning and scheduling, pp 29–37

    Google Scholar 

  • Faessler M, Fontana F, Forster C, Mueggler E, Pizzoli M, Scaramuzza D (2016) Autonomous, vision-based flight and live dense 3D mapping with a quadrotor micro aerial vehicle. J Field Robot 33(4):431–450

    Article  Google Scholar 

  • Feng L, Everett H, Borenstein J (1996) Where am I? Sensors and methods for autonomous mobile robot positioning. University of Michigan

    Google Scholar 

  • Ferguson D, Likhachev M, Stentz A (2005) A guide to heuristic-based path planning. In: Proceedings of the international workshop on planning under uncertainty for autonomous systems (International Conference on Automated Planning and Scheduling)

    Google Scholar 

  • Ferguson D, Stentz A (2006) Anytime RRTs. In: Proceedings of the international conference on intelligent robots and systems, pp 5369–5375

    Google Scholar 

  • Galceran E, Carreras M (2013) A survey on coverage path planning for robotics. Robot Auton Syst 61(12):1258–1276

    Article  Google Scholar 

  • Gohl P, Burri M, Omari S, Rehder J, Nikolic J, Achtelik M, Siegwart R (2014) Towards autonomous mine inspection. In: Proceedings of the international conference on applied robotics for the power industry, pp 1–6

    Google Scholar 

  • Grisetti G, Kummerle R, Stachniss C, Burgard W (2010) A tutorial on graph-based SLAM. IEEE Intell Transp Syst Mag 2(4):31–43

    Article  Google Scholar 

  • Henry P, Krainin M, Herbst E, Ren X, Fox D (2014) RGB-D mapping: using depth cameras for dense 3D modeling of indoor environments. In: Khatib O, Kumar V, Sukhatme G (eds) Proceedings of the international symposium on experimental robotics, ISER 2010, pp 477–491. Springer

    Google Scholar 

  • Kerl C, Sturm J, Cremers D (2013) Dense visual SLAM for RGB-D cameras. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems, pp 2100–2106

    Google Scholar 

  • La HM, Lim RS, Basily B, Gucunski N, Yi J, Maher A, Romero FA, Parvardeh H (2013) Autonomous robotic system for high-efficiency non-destructive bridge deck inspection and evaluation. In: Proceedings of the IEEE international conference on automation science and engineering, pp 1053–1058

    Google Scholar 

  • Likhachev M, Gordon GJ, Thrun S (2004) ARA: anytime A with provable bounds on sub-optimality. In: Thrun S, Saul LK, Schölkopf B (eds) Proceedings of the advances in neural information processing systems, pp 767–774. MIT Press

    Google Scholar 

  • Liu H, Darabi H, Banerjee P, Liu J (2007) Survey of wireless indoor positioning techniques and systems. IEEE Trans Syst Man Cybern Part C Appl Rev 37(6):1067–1080

    Article  Google Scholar 

  • Menendez E, Victores JG, Montero R, Martínez S, Balaguer C (2018) Tunnel structural inspection and assessment using an autonomous robotic system. Autom Constr 87:117–126

    Google Scholar 

  • Mirats JM, Garthwaite W (2010) Robotic devices for water main in-pipe inspection: a survey. J Field Robot 27(4):491–508

    Article  Google Scholar 

  • Moravec H, Elfes A (1985) High resolution maps from wide angle sonar. In: Proceedings of the IEEE international conference on robotics and automation, vol 2, pp 116–121

    Google Scholar 

  • Ortiz A, Bonnin-Pascual F, Garcia-Fidalgo E (2014) Vessel inspection: a micro-aerial vehicle-based approach. J Intell Robot Syst 76(1):151–167

    Article  Google Scholar 

  • Ortiz A, Bonnin-Pascual F, Gibbins A, Apostolopoulou P, Bateman W, Eich M, Spadoni F, Caccia M, Drikos L (2010) First steps towards a roboticized visual inspection system for vessels. In: Proceedings of the IEEE international conference on emerging technologies and factory automation, pp 1–6

    Google Scholar 

  • Ozaslan T, Loianno G, Keller J, Taylor CJ, Kumar V, Wozencraft JM, Hood T (2017) Autonomous navigation and mapping for inspection of penstocks and tunnels with MAVs. IEEE Robot Autom Lett 2(3):1740–1747

    Article  Google Scholar 

  • Pagnano A, Höpf M, Teti R (2013) A roadmap for automated power line inspection. Maintenance and repair. In: Proceedings of the conference on intelligent computation in manufacturing engineering, pp 234–239

    Google Scholar 

  • Ridao P, Carreras M, Ribas D, Garcia R (2010) Visual inspection of hydroelectric dams using an autonomous underwater vehicle. J Field Robot 27(6):759–778

    Article  Google Scholar 

  • Roslin NS, Anuar A, Jalal MFA, Sahari KSM (2012) A review: hybrid locomotion of in-pipe inspection robot. In: Proceedings of the international symposium on robotics and intelligent sensors, vol 41, pp 1456–1462

    Google Scholar 

  • Schmidt D, Berns K (2013) Climbing robots for maintenance and inspections of vertical structures—a survey of design aspects and technologies. Robot Auton Syst 61(12):1288–1305

    Article  Google Scholar 

  • Siegel M, Gunatilake P (1998) Remote enhanced visual inspection of aircraft by a mobile robot. In: Proceedings of the IEEE workshop on emerging technologies, intelligent measurement and virtual systems for instrumentation and measurement

    Google Scholar 

  • Siegwart R, Nourbakhsh IR, Scaramuzza D (2011) Introduction to autonomous mobile robots, 2nd edn. The MIT Press, Cambridge

    Google Scholar 

  • Sintov A, Avramovich T, Shapiro A (2011) Design and motion planning of an autonomous climbing robot with claws. Robot Auton Syst 59(11):1008–1019

    Article  Google Scholar 

  • Stachniss C (2009) Robotic mapping and exploration, 1st edn. Springer, Berlin/Heidelberg

    Book  Google Scholar 

  • Thrun S, Burgard W, Fox D (2005) Probabilistic robotics. The MIT Press, Cambridge

    MATH  Google Scholar 

  • Thrun S, Liu Y, Koller D, Ng AY, Ghahramani Z, Durrant-Whyte H (2004) Simultaneous localization and mapping with sparse extended information filters. Int J Robot Res 23(7–8):693–716

    Article  Google Scholar 

  • Urmson C, Baker CR, Dolan JM, Rybski P, Salesky B, Whittaker WRL, Ferguson D, Darms M (2009) Autonomous driving in traffic: boss and the urban challenge. AI Mag 30(2):17–29

    Article  Google Scholar 

  • Zelinsky A, Jarvis R, Byrne JC, Yuta S (1993) Planning paths of complete coverage of an unstructured environment by a mobile robot. In: Proceedings of the international conference on advanced robotics, pp 533–538

    Google Scholar 

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Acknowledgements

This work was partially supported by projects BUGWRIGHT2 (EU-H2020, GA 871260), ROBINS (EU-H2020, GA 779776), PGC2018-095709-B-C21 (MCIU/AEI/FEDER, UE), and PROCOE/4/2017 (Govern Balear, 50% P.O. FEDER 2014–2020 Illes Balears). This publication reflects only the authors’ views, and the European Union is not liable for any use that may be made of the information contained therein.

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Correspondence to Alberto Ortiz .

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Ortiz, A., Antich, J., Bonnin-Pascual, F. (2020). Navigation for Inspection. In: Ang, M., Khatib, O., Siciliano, B. (eds) Encyclopedia of Robotics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41610-1_87-1

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  • DOI: https://doi.org/10.1007/978-3-642-41610-1_87-1

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