Abstract
This chapter addresses the task of motion or path planning for an autonomous underwater vehicle (AUV). Once a map of the environment is built, and the vehicle has been able to localize itself, the high-level task of path planning must be achieved in order for the platform to complete its mission objectives.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
LaValle S (2011) Motion planning. IEEE Robot Autom Mag 18(1):79–89
Gasparri A, B.K., Sukhatme G (2008) A framework for multi-robot node coverage in sensor networks. Ann Math Artif Intell 52:281–305
Gonzalez E, Gerlein E (2009) Bsa-cm: a multi-robot coverage algorithm. In: Web intelligence and intelligent agent technologies, 2009. WI-IAT ’09. IEEE/WIC/ACM international joint conferences, vol 2, pp 383–386, sept 2009
Choset H (2001) Coverage for robotics - a survey of recent results. Ann Math Artif Intell 31:113–126
Acar EU, Choset H (2002) Sensor-based coverage of unknown environments: incremental construction of morse decompositions. Int J Robot Res 21:345–367
Ron Wein JvdB, Halperin D (2008) Planning high-quality paths and corridors amidst obstacles. Int J Robot Res 27:1213–1231
Cai C, Ferrari S (2009) Information-driven sensor path planning by approximate cell decomposition. IEEE Trans Syst, Man, and Cybernetics - Part B: Cybernetics 39(3):672–689
Baek S, Lee TK, Se-Young OH, Ju K (2011) Integrated on-line localization, mapping and coverage algorithm of unknown environments for robotic vacuum cleaners based on minimal sensing. Adv Robot 25(13–14):1651–1673
Li Y, Chen H, Er MJ, Wang XM (2011) Coverage path planning for uavs based on enhanced exact cellular decomposition method. Mechatronics 21:876–885
Jin J, Tang L (2011) Coverage path planning on three-dimensional terrain for arable farming. J Field Robot 28(3):424–440
Oksanen T, Visala A (2009) Coverage path planning algorithms for agricultural field machines. J Field Robot 26(8):651–668
Warren C (1990) A technique for autonomous underwater vehicle route planning. IEEE J Oceanic Eng 15(3):199–204
Biggs J, Holderbaum W (2009) Optimal kinematic control of an autonomous underwater vehicle. IEEE Trans Automatic Contr 54(7):1623–1626
Yilmaz N, Evangelinos C, Lermusiaux P, Patrikalakis N (2008) Path planning of autonomous underwater vehicles for adaptive sampling using mixed integer linear programming. IEEE J Oceanic Eng 33(4):522–537
Binney J, Krause A, Sukhatme G (2010) Informative path planning for an autonomous underwater vehicle. In: IEEE international conference on robotics and automation (ICRA), May 2010, pp 4791–4796
Cheng CT, Fallahi K, Leung H, Tse C (2010) An auvs path planner using genetic algorithms with a deterministic crossover operator. In: IEEE international conference on robotics and automation (ICRA), May 2010, pp 2995–3000
Petres C, Pailhas Y, Patron P, Petillot Y, Evans J, Lane D (2007) Path planning for autonomous underwater vehicles. IEEE Trans Robot 23(2):331–341
Petillot Y, Tena Ruiz I, Lane D (2001) Underwater vehicle obstacle avoidance and path planning using a multi-beam forward looking sonar. IEEE J Oceanic Eng 26(2):240–251
Blanco M, Wilson P (2010) Autonomous underwater vehicle minimum-time navigation in a current field. In: OCEANS 2010, pp 1–4, Sept 2010
Kruger D, Stolkin R, Blum A, Briganti J (2007) Optimal auv path planning for extended missions in complex, fast-flowing estuarine environments. In: IEEE international conference on robotics and automation 2007, pp 4265–4270, April 2007
Smith RN, Chao Y, Li PP, Caron DA, Jones BH, Sukhatme GS (2010) Planning and implementing trajectories for autonomous underwater vehicles to track evolving ocean processes based on predictions from a regional ocean model. Int J Robot Res 29(12):1475–1497
Soulignac M (2011) Feasible and optimal path planning in strong current fields. IEEE Trans Robot 27(1):89–98
Alvarez A, Caiti A, Onken R (2004) Evolutionary path planning for autonomous underwater vehicles in a variable ocean. IEEE J Oceanic Eng 29(2):418–429
Thompson D, Chien S, Chao Y, Li P, Cahill B, Levin J, Schofield O, Balasuriya A, Petillo S, Arrott M, Meisinger M (2010) Spatiotemporal path planning in strong, dynamic, uncertain currents. In: IEEE international conference on robotics and automation (ICRA) 2010, pp 4778–4783, May 2010
Stack J, Smith C (2003) Combining random and data-driven coverage planning for underwater mine detection. In: Proceedings of OCEANS 2003, vol 5, pp 2463–2468, Sept 2003
Fang C, Anstee S (2010) Coverage path planning for harbour seabed surveys using an autonomous underwater vehicle. In: OCEANS 2010 IEEE - Sydney, pp 1–8, May 2010
Choset H (2000) Coverage of known spaces: the boustrophedon cellular decomposition. Autonomous Robots 9:247–253
Kim A, Eustice R (2009) Toward auv survey design for optimal coverage and localization using the cramer rao lower bound. In: OCEANS 2009, pp 1–7, Oct 2009
Williams D (2010) On optimal auv track-spacing for underwater mine detection. In: IEEE international conference on robotics and automation (ICRA) 2010, pp 4755–4762, May 2010
Paull L, Saeedi S, Li H, Myers V (2010) An information gain based adaptive path planning method for an autonomous underwater vehicle using sidescan sonar. In: IEEE conference on automation science and engineering (CASE), pp 835–840, 2010
Lumelsky V, Stepanov A (1987) Path planning strategies for point mobile automaton moving amidst unknown obstacles of arbitrary shape. Algorithmica 2:403–430
I Kamon ER, Rivlin E (1998) Tangentbug: A range-sensor based navigation algorithm. Int J Robot Res 17(9):934–953
Choset H, Burgard W, Hutchinson S, Kantor G, Kavraki LE, Lynch K, Thrun S (2005) Principles of robot motion: theory, algorithms, and implementation. MIT Press, Cambridge
Khatib O (1986) Real-time obstacle avoidance for manipulators and mobile robots. Int J Robot Res 5:90–98
Koditschek DE, Rimon E (1990) Robot navigation functions on manifolds with boundary. Adv Appl Math 11:412–442
Barraquand J, Langlois B, Latombe C (1992) Numerical potential field techniques for robot path planning. IEEE Trans Man and Cybernetics 22:224–241
Latombe J (1991) Robot motion planning. Kluwer Academic Publishers, Norwell
Lozano-Perez T, Wesley M (1979) An algorithm for planning collision-free paths among polyhedral obstacles. Commun ACM 22(10):560–570
Aurenhammer F (1991) Voronoi diagrams a survey of a fundamental geometric structure. ACM Comput Surveys 23:345–405
Kavraki LE, Svestka P, Latombe J-C, Overmars MH (1996) Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Trans Robot Autom 12(4):566–580
Kuffner JJ, LaValle SM (2000) Rrt-connect: an efficient approach to single-query path planning. In: IEEE international conference on robotics and automation, pp 995–1001, 2000
Choset H (2000) Coverage of known spaces: the boustrophedon cellular decomposition. Autonomous Robots 9:247–253
Acar EU, Choset H, Rizzi AA, Atkar PN, Hull D (2002) Morse decompositions for coverage tasks. Int J Robotic Res 21(4):331–344
Szymczyk M, LaMothe A (2002) Mac game programming. Muska & Lipman/Premier-Trade
Srinivas S, Patnaik LM (1994) Genetic algorithms: a survey. IEEE Comput 27(6):17–26
Holland J (1945) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor
Li H, Yang S, Seto M (2009) Neural network based path planning for a multi-robot system with moving obstacles. IEEE Trans Syst, Man and Cybernetics, Part C - Appl Rev 39
Pehlivanoglu YV (2007) Path planning for autonomous uav via vibrational genetic algorithm. Aircraft Eng Aerospace Tech: Int J 79(8):532–539
Davis L (1991) Handbook on genetic algorithms. Van Nostrand Reinhold, New York
Zerr B, Fawcett J, Hopkin D (2009) Adaptive algorithm for sea mine classification. In: 3rd international conference & exhibition on underwater acoustic measurements: technologies & results, pp 319–326, 2009
Williams D, Groen J, Fox W (2011) A fast detection algorithm for autonomous mine countermeasures. In: NATO underwater research center, Nurc-fr-2011-006, Oct 2011
Chapple P (2002) Automated detection and classification in high-resolution sonar imagery for autonomous underwater vehicle operations. Dsto-gd-0537, Maritime operations division DSTO defence science and technology organisation, Dec 2002
Davies G, Signell E (2006) Espresso scientific user guide. In: NATO underwater research centre, Nurc-sp-2006-003, 2006
Grocholsky B (2002) Information-theoretic control of multiple sensor platforms. Ph.D. thesis, Australian Centre for Field Robotics, University of Sydney
Papoulis A, Pillai SU (2002) Probability, random variables and stochastic processes, 4th edn. McGraw Hill, New York
Fawcett J, Myers V, Hopkin D, Crawford A, Couillard M, Zerr B (2010) Multiaspect classification of sidescan sonar images: Four different approaches to fusing single-aspect information. IEEE J Oceanic Eng 35(4):863–876
Fawcett JA, Crawford A, Hopkin D, Myers V, Couillard M, Zerr B (2008) Multi-aspect computer-aided classification of the citadel trial side-scan sonar images. Drdc atlantic tm 2008-029, Defence R&D Canada - Atlantic, 2008
Bourque FA, Nguyen B (2011) Optimal sensor configurations for rectangular target detection. In: 9th IEEE international conference on control and automation (ICCA) 2011, pp 455–460, Dec 2011
Bays M, Shende A, Stilwell D, Redfield S (2011) A solution to the multiple aspect coverage problem. In: IEEE international conference on robotics and automation (ICRA) 2011, pp 1531–1537, May 2011
Nguyen B, Hopkin D, Yip H (2008) Autonomous underwater vehicles a transformation of mine counter-measure operations. Defense and Security Analysis 243:247–266
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media New York
About this chapter
Cite this chapter
Paull, L., Saeedi, S., Li, H. (2013). Path Planning for Autonomous Underwater Vehicles. In: Seto, M. (eds) Marine Robot Autonomy. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5659-9_4
Download citation
DOI: https://doi.org/10.1007/978-1-4614-5659-9_4
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-5658-2
Online ISBN: 978-1-4614-5659-9
eBook Packages: EngineeringEngineering (R0)