Cai W, Wu Y, Zhang M (2020) Three-dimensional obstacle avoidance for autonomous underwater robot. IEEE Sensors Letters 4(11):1-4. DOI:10.1109/LSENS.2020.3034309
Carsten J, Ferguson D, Stentz A (2006) 3D Field D:Improved path planning and replanning in three dimensions. IEEE/RSJ International Conference on Intelligent Robots & Systems
Dash AK, Chen IM, Song HY, Yang G (2003) Singularity-free path planning of parallel manipulators using clustering algorithm and line geometry. IEEE International Conference on Robotics & Automation
Dong HK (2009) Escaping route method for a trap situation in local path planning. International Journal of Control Automation & Systems 7(3):495-500. DOI:10.1007/s12555-009-0320-7
Dong J (2013) Research on firefly algorithm and its application in path planning of underwater vehicle. Master thesis, Harbin Engineering University (in Chinese)
Gasparetto A, Boscariol P, Lanzutti A, Vidoni R (2015) Path planning and trajectory planning algorithms:A general overview. Springer International Publishing
Gong JF, Peng SX (2002) Approach to Robot path planning based on numerical potential field and genetic algorithm. Journal of Tianjin University (Science and Technology), (in Chinese) DOI:10.1007/s11769-002-0038-4
Gu GC, Fu Y, Liu HB. (2005). Path planning of AUV based on genetic simulated annealing algorithm. Journal of Harbin Engineering University. (in Chinese) DOI:10.3969/j. issn. 1006-7043. 2005.01.018
Hart PE, Nilsson N, Raphael B (1972) A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science & Cybernetics 4(2):28-29. DOI:10.1145/ 1056777.1056779
Jr J, Lavalle SM (2000) RRT-connect:an efficient approach to single-query path planning. Proceedings of the 2000 IEEE International Conference on Robotics and Automation, ICRA 2000, San Francisco, USA
Kawaguchi K (2016) Deep learning without poor local minima.
Khatib O (2003) Real-time obstacle avoidance for manipulators and mobile robots. IEEE International Conference on Robotics and Automation
Lavalle SM, Kuffner JJ (2000) Rapidly-exploring random trees:progress and prospects. Algorithmic & Computational Robotics New Directions. DOI:10.1201/9781439864135-43
Li YS (2012) Research on the environmnet modeling method of the AUV path planning system. Master thesis, Harbin Engineering University (in Chinese)
Liu C, Han J, An K (2017) Dynamic path planning based on an improved RRT algorithm for roboCup robot. Robot 39(1):8-15.(in Chinese) DOI:10.13973/j.cnki.robot.2017.0008
Liu C, Zhao Y, Gao F, Liu L (2015) Three-dimensional path planning method for autonomous underwater vehicle based on modified firefly algorithm. Mathematical Problems in Engineering 2015(Pt.20):1-10. DOI:10.1155/2015/561394
Liu G, Liu P, Mu W, Wang S (2016) A path optimization algorithm for AUV using an improved ant colony algorithm with optimal energy consumption. Hsi-An Chiao Tung Ta Hsueh/Journal of Xi’an Jiaotong University, 50(10):93-98. (in Chinese) DOI:10.7652/xjtuxb201610014
Lozano-Pérez T (1990) Spatial planning:A configuration space approach. Autonomous Robot Vehicles 108-120. DOI:10.1109/TC.1983.1676196
Morris P (1993) The Breakout method for escaping from local minima. Proceedings of the 11th National Conference on Artificial Intelligence, Washington, DC, USA
Orozco-Rosas U, Montiel O, Sepúlveda R (2019a). Mobile robot path planning using membrane evolutionary artificial potential field. Applied Soft Computing. DOI:10.1016/j.asoc.2019.01.036
Orozco-Rosas U, Picos K, Ross O (2019b) Hybrid path planning algorithm based on membrane pseudo-bacterial potential field for autonomous mobile robots. IEEE Access 7(1):156787-156803.DOI:10.1109/ACCESS.2019.2949835
Sariff N, Buniyamin N (2006) An overview of autonomous mobile robot path planning algorithms. Conference on Research & Development
Song JZ, Dai B, Shan EZ, He HG (2010) An improved RRT path planning algorithm. Acta Electronica Sinica 38:225-228. (in Chinese) DOI:CNKI:SUN:DZXU.0.2010-S1-040
Sun Y, Wang L, Wu J, Ran X (2020) A general overview of path planning methods for autonomous underwater vehicle. Ship Science an Technology, 42(4):1-7. (in Chinese) DOI:CNKI:SUN:JCKX.0.2020-07-002
Tanakitkorn K, Wilson PA, Turnock SR, Phillips AB (2014) Gridbased GA path planning with improved cost function for an overactuated hover-capable AUV. AUV 2014
Volpe R, Khosla P (1990) Manipulator control with superquadric artificial potential functions:theory and experiments. Systems Man & Cybernetics IEEE Transactions 20(6):1423-1436. DOI:10.1109/21.61211
Wang H, Wu X, Shi X (2008) Global planning path method of AUV based on ant colony optimization Algorithm. Shipbuilding of China, 49(2):88-93.(in Chinese) DOI:10.1080/02699930701273823
Wang LL, Sui ZZ, Pu ZQ, Liu Z, Yi JQ (2020) An Improved RRT algorithm for multi-robot formation path planning. Acta Electronica Sinica 48:60-67. (in Chinese) DOI:10.3969/j.issn.0372-2112.2020.11.007
Wang Q (2014) Research on rapidly-exploring random trees based global path planning and its application. Master thesis, National University of Defense Technology. (in Chinese)
Xu H, Li Y (2010) An immune genetic algorithm for AUV local path planning. International Society of Offshore and Polar Engineers Xu M, Franti P (2004) A heuristic K-means clustering algorithm by kernel PCA. 2004 International Conference on Image Processing, ICIP’ 04.
Xu YR, Yao YZ (2008) Research on AUV global path planning considering ocean current. Shipbuilding of China 49(4):109-114.(in Chinese) DOI:10.3969/j.issn.1000-4882.2008.04.014
Zhu DQ, Sun B, Li L (2015) Algorithm for AUV’s 3-D path planning andsafeobstacleavoidancebasedonbiologicalinspiredmodel.Control & Decision 30(5):798-806. (in Chinese) DOI:10. 13195/j.kzyjc.2014.0339