Research On Path Planning Of Unmanned Underwater Vehicle For Long-Duration Missions Based On Energy Consumption Optimization In Complex Ocean Environments

Unmanned underwater vehicles(UUVs)are a class of submerged marine robots using various enabling technologies to navigate and perform various tasks,which have been more and more used in a variety military,scientific research and commercial applications.UUV's autonomy has been challenged by increasingly complex mission demands.In practical applications,due to the battery capacity of UUV is limited,the energy constraint to the implementation of long-term observation or monitoring has become a technical bottleneck that needs to be addressed urgently.In addition,the UUV actual sailing speed and the circulation velocity in the ocean are basically in the same dimension,so the circulation will seriously affect the UUV efficiency and energy consumption.In this paper,energy consumption is used as the optimization object to study the UUV long-range path planning method under the influence of complex marine environment.The main research work is as follows:According the classification criterion made by the duration of missions,a detailed introduction of UUV product status has been made.Then based on the four optimization objects of travel time,energy consumption,safety and information sampling,this paper analyzed the current situation of UUV path planning research.And a method that contains stochastic annular spatial decomposition and the path control nodes setting for UUV path planning in twodimensional and three-dimensional marine environment are extended,according to some part of the present research method,which help to effectively reduce the computational complexity and increase the searching breadth of the algorithm.Combined with the B-Spline,using the subdivision to complete the path planning generated in the two-dimensional and threedimensional environment and to ensure a good track smoothness,meeting the actual needs of the UUV trajectory tracking control.In order to complete the path planning considering complex marine environment,this paper used a method based on the superposition of multiple viscous Lamb vorticity to establish a marine environment model which can simulate the ocean circulation in two-and threedimensional space with reasonable accuracy.Aiming at the optimization of energy consumption,the UUV energy consumption model in two-dimensional and three-dimensional space is established.In order to prove the impact of energy consumption on UUV task execution,a scenario of UUV information sampling is designed and a multi-objective optimization model based on UUV energy consumption and information sampling is established.Combined with Particle Swarm Optimization(PSO),Quantum-behaved Particle Swarm Optimization(QPSO)and Multi-objective Particle Swarm Optimization(MOPSO),this paper completed the optimization of a variety of designed task execution cases,according to the needs of mission cases to generate the UUV energy consumption optimal trajectory.In this paper,Adaptive Quantum-behaved Particle Swarm Optimization(AQPSO)is proposed in a modified way,which is better at computational complexity and computational complexity than the traditional PSO and QPSO algorithms.In the meantime,a hybrid MOPSO-FCE algorithm based on MOPSO and Fuzzy Comprehensive Evaluation(FCE)is proposed in this paper.The complete process of generating solution from non-dominated solutions to the actual demand of UUV missions is realized.Finally,a series of Monte Carlo simulations are used to verify the effectiveness of each optimization algorithm in generating the optimal UUV energy consumption navigation path and to prove the excellent performance of the improved algorithm.