Definition
Vision for the Marine Environment refers to underwater imaging hardware and algorithms that enable the perception of the subsea environment for marine science applications, inspection and intervention.
Overview
For a long time, optical cameras have been used in ROVs to provide the user with visual feedback of the operational scene. Conversely, AUVs have been traditionally equipped with sonar imaging systems, for two main reasons. First, the range of acoustic imaging is significantly higher, and second, as a consequence, they can work at a safer altitude, while the AUV follows the bottom profile. Nevertheless, during the last decades, vision systems have become smaller and more power-efficient, and the robot hardware has become more powerful and capable of storing the images onboard. Nowadays, commercial AUVs may be equipped with vision systems able to provide high-resolution seafloor imagery in...
References
Bailey T, Durrant-Whyte H (2006) Simultaneous localization and mapping (SLAM): part II. IEEE Robot Autom Mag 13(3):108–117
Bingham B, Foley B, Singh H, Camilli R, Delaporta K, Eustice R, Mallios A, Mindell D, Roman CN, Sakellariou D (2010) Robotic tools for deep water archaeology: surveying an ancient shipwreck with an autonomous underwater vehicle. J Field Robot 27(6):702–717
Bodenmann A, Thornton B, Ura T (2017) Generation of high-resolution three-dimensional reconstructions of the seafloor in color using a single camera and structured light. J Field Robot 34(5):833–851
Bosch J, Gracias N, Ridao P, Ribas D (2015) Omnidirectional underwater camera design and calibration. Sensors 15(3):6033–6065
Bosch J, Gracias N, Ridao P, Istenič K, Ribas D (2016) Close-range tracking of underwater vehicles using light beacons. Sensors 16(4):429
Bryson M, Johnson-Roberson M, Pizarro O, Williams S (2012) Repeatable robotic surveying of marine benthic habitats for monitoring long-term change. In: Workshop on robotics for environmental monitoring at robotics: science and systems (RSS)
Camilli R, Nomikou P, Escartin J, Ridao P, Mallios A, Kilias S, Argyraki A (2015) The Kallisti Limnes, carbon dioxide-accumulating subsea pools. Sci Rep, pp 1-9
Campos R, Gracias N, Ridao P (2016) Underwater multi-vehicle trajectory alignment and mapping using acoustic and optical constraints. Sensors 16(3):387
Chantler MJ, Clark J, Umasuthan M (1997) Calibration and operation of an underwater laser triangulation sensor: the varying baseline problem. Opt Eng 36(9):2604
Chaves SM, Galceran E, Ozog P, Walls JM, Eustice RM (2017) Pose-graph SLAM for underwater navigation. Springer, Cham, pp 143–160
Corke P, Detweiler C, Dunbabin M, Hamilton M, Rus D, Vasilescu I (2007) Experiments with underwater robot localization and tracking. In: Proceedings 2007 IEEE international conference on robotics and automation, pp 4556–4561
Dansereau DG, Mahon I, Pizarro O, Williams SB (2011) Plenoptic flow: closed-form visual odometry for light field cameras. In: 2011 IEEE/RSJ international conference on intelligent robots and systems, pp 4455–4462
Durrant-Whyte H, Bailey T (2006) Simultaneous localization and mapping: part I. IEEE Robot Autom Mag 13(2):99–110
Escartin J, Barreyre T, Cannat M, Garcia R, Gracias N, Deschamps A, Salocchi A, Sarradin P-M, Ballu V (2015) Hydrothermal activity along the slow-spreading lucky strike ridge segment (Mid-Atlantic Ridge): distribution, heatflux, and geological controls. Earth Planet Sci Lett 431:173–185
Eustice R, Singh H, Leonard J, Walter M (2006a) Visually mapping the RMS Titanic: conservative covariance estimates for SLAM information filters. Int J Robot Res 25(12):1223–1242
Eustice RM, Singh H, Leonard JJ (2006b) Exactly sparse delayed-state filters for view-based SLAM. IEEE Trans Robot 22(6):1100–1114
Ferreira F, Veruggio G, Caccia M, Bruzzone G (2012) A comparison between different feature-based methods for ROV vision-based speed estimation. In: Proceedings of the 3rd IFAC workshop on navigation, guidance and control of underwater vehicles, pp 325–330
Ferrer J, Elibol A, Delaunoy O, Gracias N, Garcia R (2007) Large-area photo-mosaics using global alignment and navigation data. In: Proceedings of the IEEE OCEANS conference, Vancouver
Fraundorfer F, Scaramuzza D (2012) Visual odometry : part II: matching, robustness, optimization, and applications. IEEE Robot Autom Mag 19(2):78–90
Garcia R, Puig J, Ridao P, Cufi X (2002) Augmented State Kalman filtering for AUV navigation. In: Proceedings of 2002 IEEE international conference on robotics and automation, vol 4, pp 4010–4015
Gracias N, Zwaan S, Bernardino A, Santos-Victor J (2003) Mosaic based navigation for autonomous underwater vehicles. J Oceanic Eng 28(4):609–624
Gracias N, Ridao P, Garcia R, Escartín J, L’Hour M, Cibecchini F, Campos R, Carreras M, Ribas D, Palomeras N, Magi L, Palomer A, Nicosevici T, Prados R, Hegedüs R, Neumann L, de Filippo F, Mallios A (2013) Mapping the Moon: using a lightweight AUV to survey the site of the 17th century ship ‘La Lune’. In: Proceedings of the IEEE OCEANS 2013 conference, Bergen
Hildebrandt M, Kirchner F (2010) IMU-aided stereo visual odometry for ground-tracking AUV applications. In: Proceedings of the IEEE OCEANS 2010 conference – Sydney
Horgan J, Toal D (2009) Computer vision applications in the navigation of unmanned underwater vehicles. In: Underwater vehicles (InTech)
Inglis G, Smart C, Vaughn I, Roman C (2012) A pipeline for structured light bathymetric mapping. In: IEEE/RSJ international conference on intelligent robots and systems, pp 4425–4432
Istenič K, Ila V, Polok L, Gracias N, García R (2017) Mission-time 3D reconstruction with quality estimation. In: Proceedings of the MTS/IEEE OCEANS 2017 conference, Aberdeen
Johnson-Roberson M, Pizarro O, Willams S (2009) Towards large scale optical and acoustic sensor integration for visualization. In: Proceedings of the IEEE Oceans 2009-Europe conference, Bremen
Kato H, Billinghurst M (1999) Marker tracking and HMD calibration for a video-based augmented reality conferencing system. In: Proceedings of the 2nd IEEE and ACM international workshop on augmented reality, IWAR’99. IEEE Computer Society, Washington, DC, pp 85–94
Kim A, Eustice RM (2013) Real-time visual SLAM for autonomous underwater hull inspection using visual saliency. IEEE Trans Robot 29(3):719–733
Kocak D, Caimi F, Das P, Karson J (1999) A 3-D laser line scanner for outcrop scale studies of seafloor features. Proc OCEANS Conf 3:1105–1114
Krupínski S, Allibert G, Hua MD, Hamel T (2017) An inertial-aided homography-based visual servo control approach for (almost) fully actuated autonomous underwater vehicles. IEEE Trans Robot 33(5):1041–1060
Lots JF, Lane DM, Trucco E, Chaumette F (2001) A 2D visual servoing for underwater vehicle station keeping. In: Proceedings 2001 ICRA IEEE international conference on robotics and automation, vol 3, pp 2767–2772
Łuczyński T, Pfingsthorn M, Birk A (2017) The pinax-model for accurate and efficient refraction correction of underwater cameras in flat-pane housings. Ocean Eng 133(Supplement C):9–22
Marchand E, Chaumette F, Spindler F, Perrier M (2001) Controlling an uninstrumented ROV manipulator by visual servoing. In: MTS/IEEE Oceans 2001 conference, Honolulu, vol 2, pp 1047–1053
Massot-Campos M, Oliver-Codina G (2014) Underwater laser-based structured light system for one-shot 3D reconstruction. In: IEEE sensors 2014 proceedings, pp 1138–1141
Negahdaripour S, Zhang H, Firoozfam P, Oles J (2001) Utilizing panoramic views for visually guided tasks in underwater robotics applications. In Proceedings of the MTS/IEEE Oceans 2001 conference, Honolulu, vol 4, pp 2593–2600
Ortiz A, Antich J, Oliver G (2011) A particle filter-based approach for tracking undersea narrow telecommunication cables. Mach Vis Appl 22(2):283–302
Palomer A, Ridao P, Ribas D, Forest J (2017) Underwater 3D laser scanners: the deformation of the plane. Springer International Publishing, Cham, pp 73–88
Palomeras N, Nagappa S, Ribas D, Gracias N, Carreras M (2013) Vision-based localization and mapping system for AUV intervention. In: Proceedings of the IEEE oceans 2013 conference, Bergen
Palomeras N, Peñalver A, Massot-Campos M, Negre PL, Fernández JJ, Ridao P, Sanz PJ, Oliver-Codina G (2016) I-AUV docking and panel intervention at sea. Sensors 16(10):1673
Pfingsthorn M, Birk A, Schwertfeger S, Buelow H, Pathak K (2010) Maximum likelihood mapping with spectral image registration. In: Proceedings of the IEEE international conference on robotics and automation ICRA2010, pp 4282–4287
Prados R, Garcia R, Neumann L (2014) Image blending techniques and their application in underwate mosaicing. Springer, Cham
Prats M, Fernandez JJ, Sanz PJ (2012) Combining template tracking and laser peak detection for 3D reconstruction and grasping in underwater environments. IEEE Int Conf Intell Robot Syst 1:106–112
Remondino F, Spera MG, Nocerino E, Menna F, Nex F, Gonizzi-Barsanti S (2013) Dense image matching: comparisons and analyses. In: Proceedings of IEEE conference on digital heritage, vol 1, pp 47–54
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
Roman C, Inglis G, Rutter J (2010) Application of structured light imaging for high resolution mapping of underwater archaeological sites. In: OCEANS 2010 IEEE – Sydney
Singh H, Roman C, Pizarro O, Eustice R, Can A (2007) Towards high-resolution imaging from underwater vehicles. Int J Robot Res 26(1):55–74
Tarel J-P, Hautière N (2009) Fast visibility restoration from a single color or gray level image. In: Proceedings of IEEE international conference on computer vision (ICCV’09), Kyoto, pp 2201–2208
Treibitz T, Schechner YY (2009) Active polarization descattering. IEEE Trans Pattern Anal Mach Intell 31(3):385–399
Vallicrosa G, Bosch J, Palomeras N, Ridao P, Carreras M, Gracias N (2016) Autonomous homing and docking for AUVs using range-only localization and light beacons. IFAC-PapersOnLine 49(23):54–60. 10th IFAC CAMS 2016
Waechter M, Moehrle N, Goesele M (2014) Let there be color! large-scale texturing of 3D reconstructions. In: Proceedings of the 13th ECCV conference, Zurich, pp 836–850
Weidemann A, Fournier G, Forand L, Mathieu P (2005) Optical image sensing through turbid water. In: Proceedings of SPIE, vol 5780, pp 59–70
Williams S, Pizarro O, Jakuba M, Johnson C, Barrett N, Babcock R, Kendrick G, Steinberg P, Heyward A, Doherty P, Mahon I, Johnson-Roberson M, Steinberg D, Friedman A (2012) Monitoring of benthic reference sites: using an autonomous underwater vehicle. IEEE Robot Autom Mag 19(1):73–84
Wirth S, Carrasco P, Codina G (2013) Visual odometry for autonomous underwater vehicles. In: Proceedings of the MTS/IEEE Oceans 2013 conference, Bergen
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Gracias, N., Ridao, P., Garcia, R., Carreras, M. (2018). Vision for the Marine Environment. In: Ang, M., Khatib, O., Siciliano, B. (eds) Encyclopedia of Robotics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41610-1_17-1
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