Abstract
Due to the unavailability of GPS signal, it is more urgent to develop the autonomous navigation capability for the underwater vehicles. In this paper, we summarize the development status of underwater SLAM (simultaneous localization and mapping) system. Different from the terrestrial or aerial SLAM that largely depends on the optical sensors, the underwater SLAM system mainly uses the acoustic sensors, i.e., sonars, to watch the environment. With respect to the general SLAM system, which is mainly composed of the front-end local data-association and the back-end global error adjustment, we briefly survey recent progress in sonar image registration and the loop closure detection. Furthermore, some heuristic problems are posed in the conclusion.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Aykin, M., Negahdaripour, S.: On feature extraction and region matching for forward scan sonar imaging. In: 2012 Oceans, pp. 1–9. IEEE (2012)
Barkby, S., Williams, S.B., Pizarro, O., Jakuba, M.V.: A featureless approach to efficient bathymetric SLAM using distributed particle mapping. J. Field Robot. 28(1), 19–39 (2011)
Belcher, E., Hanot, W., Burch, J.: Dual-frequency identification sonar (DIDSON). In: Proceedings of the 2002 Interntional Symposium on Underwater Technology (Cat. No. 02EX556), pp. 187–192. IEEE (2002)
Besl, P.J., McKay, N.D.: Method for registration of 3-D shapes. In: Sensor Fusion IV: Control Paradigms and Data Structures, vol. 1611, pp. 586–607. International Society for Optics and Photonics (1992)
Bingham, B., et al.: Robotic tools for deep water archaeology: surveying an ancient shipwreck with an autonomous underwater vehicle. J. Field Robot. 27(6), 702–717 (2010)
Bosse, M., Zlot, R.: Map matching and data association for large-scale two-dimensional laser scan-based SLAM. Int. J. Robot. Res. 27(6), 667–691 (2008)
Chen, L., Wang, S., Hu, H., Gu, D., Liao, L.: Improving localization accuracy for an underwater robot with a slow-sampling sonar through graph optimization. IEEE Sens. J. 15(9), 5024–5035 (2015)
Elfes, A.: Sonar-based real-world mapping and navigation. IEEE J. Robot. Autom. 3(3), 249–265 (1987)
Eustice, R.M., Singh, H., Leonard, J.J., Walter, M.R.: Visually mapping the RMS titanic: conservative covariance estimates for SLAM information filters. Int. J. Robot. Res. 25(12), 1223–1242 (2006)
Fairfield, N., Kantor, G., Wettergreen, D.: Real-time SLAM with octree evidence grids for exploration in underwater tunnels. J. Field Robot. 24(1–2), 03–21 (2007)
He, B., et al.: Autonomous navigation based on unscented-FastSLAM using particle swarm optimization for autonomous underwater vehicles. Measurement 71, 89–101 (2015)
Henson, B.T., Zakharov, Y.V.: Attitude-trajectory estimation for forward-looking multibeam sonar based on acoustic image registration. IEEE J. Oceanic Eng. 99, 1–14 (2018)
Hernández, E., Ridao, P., Ribas, D., Mallios, A.: Probabilistic sonar scan matching for an AUV. In: 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 255–260. IEEE (2009)
Hernàndez Bes, E., Ridao Rodríguez, P., Ribas Romagós, D., Batlle i Grabulosa, J.: MSISpIC: a probabilistic scan matching algorithm using a mechanical scanned imaging sonar. J. Phys. Agents 3(1), 3–11 (2009)
Hurtós, N., Palomeras, N., Carrera, A., Carreras, M.: Autonomous detection, following and mapping of an underwater chain using sonar. Ocean Eng. 130, 336–350 (2017)
Hurtós, N., Ribas, D., Cufí, X., Petillot, Y., Salvi, J.: Fourier-based registration for robust forward-looking sonar mosaicing in low-visibility underwater environments. J. Field Robot. 32(1), 123–151 (2015)
Inglis, G., Smart, C., Vaughn, I., Roman, C.: A pipeline for structured light bathymetric mapping. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4425–4432. IEEE (2012)
Jiang, M., Song, S., Tang, F., Li, Y., Liu, J., Feng, X.: Scan registration for underwater mechanical scanning imaging sonar using symmetrical Kullback-Leibler divergence. J. Electron. Imaging 28(1), 013026 (2019)
Johannsson, H., Kaess, M., Englot, B., Hover, F., Leonard, J.: Imaging sonar-aided navigation for autonomous underwater harbor surveillance. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4396–4403. IEEE (2010)
Kim, K., Neretti, N., Intrator, N.: Mosaicing of acoustic camera images. IEE Proc.-Radar Sonar Navig. 152(4), 263–270 (2005)
Kimball, P.W., Rock, S.M.: Mapping of translating, rotating icebergs with an autonomous underwater vehicle. IEEE J. Oceanic Eng. 40(1), 196–208 (2015)
Kinsey, J.C., Eustice, R.M., Whitcomb, L.L.: A survey of underwater vehicle navigation: recent advances and new challenges. In: IFAC Conference of Manoeuvering and Control of Marine Craft, vol. 88, pp. 1–12 (2006)
Latif, Y., Cadena, C., Neira, J.: Robust loop closing over time for pose graph SLAM. Int. J. Robot. Res. 32(14), 1611–1626 (2013)
Ma, T., Li, Y., Wang, R., Cong, Z., Gong, Y.: Auv robust bathymetric simultaneous localization and mapping. Ocean Eng. 166, 336–349 (2018)
Mallios, A., Ridao, P., Ribas, D., Carreras, M., Camilli, R.: Toward autonomous exploration in confined underwater environments. J. Field Robot. 33(7), 994–1012 (2016)
Mallios, A., Ridao, P., Ribas, D., Hernández, E.: Scan matching SLAM in underwater environments. Auton. Robot. 36(3), 181–198 (2014)
Massot-Campos, M., Oliver, G., Bodenmann, A., Thornton, B.: Submap bathymetric SLAM using structured light in underwater environments. In: 2016 IEEE/OES Autonomous Underwater Vehicles (AUV), pp. 181–188. IEEE (2016)
Melo, J., Matos, A.: Survey on advances on terrain based navigation for autonomous underwater vehicles. Ocean Eng. 139, 250–264 (2017)
Montesano, L., Minguez, J., Montano, L.: Probabilistic scan matching for motion estimation in unstructured environments. In: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3499–3504. IEEE (2005)
Muhammad, N., Fuentes-Perez, J.F., Tuhtan, J.A., Toming, G., Musall, M., Kruusmaa, M.: Map-based localization and loop-closure detection from a moving underwater platform using flow features. Auton. Robots 43(6), 1419–1434 (2019)
Negahdaripour, S., Firoozfam, P., Sabzmeydani, P.: On processing and registration of forward-scan acoustic video imagery. In: The 2nd Canadian Conference on Computer and Robot Vision (CRV 2005), pp. 452–459. IEEE (2005)
Neira, J., Tardós, J.D.: Data association in stochastic mapping using the joint compatibility test. IEEE Trans. Robot. Autom. 17(6), 890–897 (2001)
Norgren, P., Skjetne, R.: A multibeam-based slam algorithm for iceberg mapping using auvs. IEEE Access 6, 26318–26337 (2018)
Ozog, P., Carlevaris-Bianco, N., Kim, A., Eustice, R.M.: Long-term mapping techniques for ship hull inspection and surveillance using an autonomous underwater vehicle. J. Field Robot. 33(3), 265–289 (2016)
Palomer, A., Ridao, P., Ribas, D.: Multibeam 3D underwater slam with probabilistic registration. Sensors 16(4), 560 (2016)
Paull, L., Saeedi, S., Seto, M., Li, H.: Auv navigation and localization: a review. IEEE J. Oceanic Eng. 39(1), 131–149 (2014)
Ribas, D., Ridao, P., Tardós, J.D., Neira, J.: Underwater SLAM in man-made structured environments. J. Field Robot. 25(11–12), 898–921 (2008)
Roman, C., Singh, H.: A self-consistent bathymetric mapping algorithm. J. Field Robot. 24(1–2), 23–50 (2007)
Roman, C.N.: Self consistent bathymetric mapping from robotic vehicles in the deep ocean. Ph.D. thesis, Massachusetts Institute of Technology (2005)
Santos, M.M., Zaffari, G.B., Ribeiro, P.O., Drews-Jr, P.L., Botelho, S.S.: Underwater place recognition using forward-looking sonar images: a topological approach. J. Field Robot. 36(2), 355–369 (2019)
Song, S., Herrmann, J.M., Si, B., Liu, K., Feng, X.: Two-dimensional forward-looking sonar image registration by maximization of peripheral mutual information. Int. J. Adv. Robot. Syst. 14(6), 1–17 (2017)
Stutters, L., Liu, H., Tiltman, C., Brown, D.J.: Navigation technologies for autonomous underwater vehicles. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 38(4), 581–589 (2008)
White, C., Hiranandani, D., Olstad, C.S., Buhagiar, K., Gambin, T., Clark, C.M.: The malta cistern mapping project: underwater robot mapping and localization within ancient tunnel systems. J. Field Robot. 27(4), 399–411 (2010)
Williams, S.B., Newman, P., Rosenblatt, J., Dissanayake, G., Durrant-Whyte, H.: Autonomous underwater navigation and control. Robotica 19(5), 481–496 (2001)
Xie, L., Wang, S., Markham, A., Trigoni, N.: GraphTinker: outlier rejection and inlier injection for pose graph SLAM. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 6777–6784. IEEE (2017)
Acknowledgements
The work is supported by the Strategic Priority Program of the Chinese Academy of Sciences (No. XDC03060105, No. XDA13030203), the State Key Laboratory of Robotics of China (No. 2017-Z010), the National Key Research and Development Program of China (No. 2016YFC0300801, No. 2016YFC0300604, No. 2016YFC0301601), the project of “R&D Center for Underwater Construction Robotics”, funded by the Ministry of Ocean and Fisheries (MOF) and Korea Institute of Marine Science & Technology Promotion (KIMST), Korea (No. PJT200539), the Public science and technology research funds projects of ocean (No. 201505017).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Jiang, M., Song, S., Li, Y., Jin, W., Liu, J., Feng, X. (2019). A Survey of Underwater Acoustic SLAM System. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11741. Springer, Cham. https://doi.org/10.1007/978-3-030-27532-7_14
Download citation
DOI: https://doi.org/10.1007/978-3-030-27532-7_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-27531-0
Online ISBN: 978-3-030-27532-7
eBook Packages: Computer ScienceComputer Science (R0)