Path planning of multiple autonomous marine vehicles for adaptive sampling using Voronoi-based ant colony optimization
Tài liệu tham khảo
Das, 2016, Cooperative formation control of autonomous underwater vehicles: An overview, Int. J. Automat. Comput., 13, 199, 10.1007/s11633-016-1004-4
Rudnick, 2016, Ocean research enabled by underwater gliders, Ann. Rev. Mar. Sci., 8, 519, 10.1146/annurev-marine-122414-033913
Nad, 2015, Navigation, guidance and control of an overactuated marine surface vehicle, Annu. Rev. Control, 40, 172, 10.1016/j.arcontrol.2015.08.005
Zeng, 2015, A survey on path planning for persistent autonomy of autonomous underwater vehicles, Ocean Eng., 110, 303, 10.1016/j.oceaneng.2015.10.007
Liu, 2015, Unmanned surface vehicles: An overview of developments and challenges, Annu. Rev. Control, 41, 71, 10.1016/j.arcontrol.2016.04.018
Ryan, 2010, USC CINAPS Builds bridges observing and monitoring the southern california, IEEE Robot. Autom. Mag., 17, 20, 10.1109/MRA.2010.935795
Mahmoudzadeh, 2018, UUV’s hierarchical DE-based motion planning in a semi dynamic underwater wireless sensor network, IEEE Trans. Cybern., 1, 10.1109/TCYB.2018.2837134
Subramani, 2016, Energy-optimal path planning by stochastic dynamically orthogonal level-set optimization, Ocean Model., 100, 57, 10.1016/j.ocemod.2016.01.006
Zeng, 2016, A comparison of optimization techniques for AUV path planning in environments with ocean currents, Robot. Auton. Syst., 82, 61, 10.1016/j.robot.2016.03.011
Eichhorn, 2015, Optimal routing strategies for autonomous underwater vehicles in time-varying environment, Robot. Auton. Syst., 67, 33, 10.1016/j.robot.2013.08.010
Garau, 2005, Path planning of autonomous underwater vehicles in current fields with complex spatial variability: an a* approach, 194
Hollinger, 2014, Sampling-based robotic information gathering algorithms, Int. J. Robot. Res., 33, 1271, 10.1177/0278364914533443
Yilmaz, 2008, Path planning of autonomous underwater vehicles for adaptive sampling using mixed integer linear programming, IEEE J. Ocean. Eng., 33, 522, 10.1109/JOE.2008.2002105
Smith, 2011, Persistent ocean monitoring with underwater gliders: Adapting sampling resolution, J. Field Robot., 28, 714, 10.1002/rob.20405
Ferri, 2015, Mission planning and decision support for underwater glider networks: A sampling on-demand approach, Sensors (Switzerland), 16, 10.3390/s16010028
Das, 2015, Data-driven robotic sampling for marine ecosystem monitoring, Int. J. Robot. Res., 34, 1435, 10.1177/0278364915587723
Ma, 2017, Data-driven learning and planning for environmental sampling, J. Field Robot.
Ma, 2016, An information-driven and disturbance-aware planning method for long-term ocean monitoring, 2102
Zhou, 2017, Adaptive re-planning of AUVs for environmental sampling missions: A Fuzzy decision support system based on multi-objective particle swarm optimization, Int. J. Fuzzy Syst.
Zeng, 2018, Rendezvous path planning for multiple autonomous marine vehicles, IEEE J. Ocean. Eng., 43, 640, 10.1109/JOE.2017.2723058
Moon, 2015, Decentralized information-theoretic task assignment for searching and tracking of moving targets, 1031
Kovács, 2016, A novel potential field method for path planning of mobile robots by adapting animal motion attributes, Robot. Auton. Syst., 82, 24, 10.1016/j.robot.2016.04.007
Dijkstra, 1959, A note on two problems in connection with graphs, 269
Fu, 2018, An improved a* algorithm for the industrial robot path planning with high success rate and short length, Robot. Auton. Syst., 106, 26, 10.1016/j.robot.2018.04.007
Ferguson, 2006, Using interpolation to improve path planning : The field D * algorithm, J. Field Robot., 23, 79, 10.1002/rob.20109
Karaman, 2010, Sampling-based algorithms for optimal motion planning, Int. J. Robot. Res., 30, 20
Elbanhawi, 2014, Sampling-based robot motion planning: A review, IEEE Access, 2, 56, 10.1109/ACCESS.2014.2302442
Aghababa, 2012, Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles, J. Mar. Sci. Appl., 11, 378, 10.1007/s11804-012-1146-x
Zeng, 2014, Shell space decomposition based path planning for AUVs operating in a variable environment, Ocean Eng., 91, 181, 10.1016/j.oceaneng.2014.09.001
Blum, 2005, Ant colony optimization: Introduction and recent trends, Phys. Life Rev., 2, 353, 10.1016/j.plrev.2005.10.001
Marinakis, 2017, A hybrid particle swarm optimization variable neighborhood search algorithm for constrained shortest path problems, European J. Oper. Res., 261, 819, 10.1016/j.ejor.2017.03.031
YongBo, 2017, Three-dimensional unmanned aerial vehicle path planning using modified wolf pack search algorithm, Neurocomputing, 266, 445, 10.1016/j.neucom.2017.05.059
Ma, 1995, Parameterization of randomly measured points for least squares fitting of b-spline curves and surfaces, Comput. Aided Des., 27, 663, 10.1016/0010-4485(94)00018-9
Arzamendia, 2017, An evolutionary approach to constrained path planning of an autonomous surface vehicle for maximizing the covered area of Ypacarai Lake, Soft Comput., 1
Dorigo, 1996, Ant system: Optimization by a colony of cooperating agents, IEEE Trans. Syst. Man Cybern., 26, 1, 10.1109/3477.484436
Cui, 2016, Mutual information-based multi-AUV path planning for scalar field sampling using multidimensional RRT*, IEEE Trans. Syst. Man Cybern. Syst., 46, 993, 10.1109/TSMC.2015.2500027
Ammar, 2016, Relaxed Dijkstra and A* with linear complexity for robot path planning problems in large-scale grid environments, Soft Comput., 20, 4149, 10.1007/s00500-015-1750-1
Perez-Carabaza, 2018, Ant colony optimization for multi-UAV minimum time search in uncertain domains, Appl. Soft Comput. J., 62, 789, 10.1016/j.asoc.2017.09.009
MahmoudZadeh, 2018, Online path planning for AUV rendezvous in dynamic cluttered undersea environment using evolutionary algorithms, Appl. Soft Comput., 70, 929, 10.1016/j.asoc.2017.10.025
Zeng, 2015, Efficient path re-planning for AUVs operating in spatiotemporal currents, J. Intell. Robot. Syst., Theory Appl., 79, 135, 10.1007/s10846-014-0104-z
Yazdani, 2017, IDVD-based trajectory generator for autonomous underwater docking operations, Robot. Auton. Syst., 92, 12, 10.1016/j.robot.2017.02.001
Cao, 2016, Toward optimal rendezvous of multiple underwater gliders: 3D path planning with combined sawtooth and spiral motion, J. Intell. Robot. Syst., Theory Appl., 1
Cao, 2016, Nonlinear multiple-input-multiple-output adaptive backstepping control of underwater glider systems, Int. J. Adv. Robot. Syst., 13, 1, 10.1177/1729881416669484
Yu, 2017, Nonlinear guidance and fuzzy control for three-dimensional path following of an underactuated autonomous underwater vehicle, Ocean Eng., 146, 457, 10.1016/j.oceaneng.2017.10.001
Xiang, 2017, On intelligent risk analysis and critical decision of underwater robotic vehicle, Ocean Eng., 140, 453, 10.1016/j.oceaneng.2017.06.020