Multi-unmanned surface vehicle (USV) group coordinated collision avoidance planning method based on genetic algorithm

Abstract

The invention discloses a multi-unmanned surface vehicle (USV) group coordinated collision avoidance planning method based on a genetic algorithm, and belongs to the technical field of USV control. The method provided by the invention comprises the steps of firstly performing initialization coding on a speed adjustment and a heading adjustment of a USV and setting other control parameters by usinga float-point coding mode; then building an evaluation function, computing the evaluation function value of each individual of a group so as to perform roulette selection, discrete crossing and Gaussian mutation genetic operations on the individual of the group, and building an iteration process to acquire an optimal solution; and at last building a USV collision avoidance plan simulation software platform by using QT software, adding a radar detection module and the genetic algorithm, and designing a typical simulation case to verify the effectiveness of the algorithm. According to the method provided by the invention, the problems that the genetic algorithm is poor in timeliness, trapping in local optimum and premature to converge, and in the genetic algorithm, the offspring optimalityis inferior to the parent optimality, and the bad navigation problems of large angle steering and large-range acceleration and deceleration during a sailing process are solved.

Description

technical field [0001] The invention belongs to the technical field of USV control, and in particular relates to a multi-USV group cooperative collision avoidance planning method based on a genetic algorithm. Background technique [0002] With the development of modern science and technology, human beings develop and utilize marine resources in various ways. The USV (unmanned aircraft) designed for non-combat naval activities such as combat in offshore shallow waters and collect meteorological and ocean data, etc. Surface boats) stand out. USVs are often used to perform various special tasks such as military activities, maritime supervision, and maritime safety cruises that are not suitable for manned platforms in severe and complex marine environments. However, for some complex, dynamic, and difficult tasks , a single USV is difficult to do. In this case, multi-USVs are gradually being valued for their overall advantages. Realizing the collision avoidance function is an ...

AI Technical Summary

Problems solved by technology

[0003] Defects of the existing technology: Genetic algorithm, as an intelligent global search algorithm, is applied to USV objects for collision avoidance planning, and there are problems such as falling into local optimum, premature convergence, and the optimum of the offspring is inferior to the optimum of the parent.

On the other hand, the number of algorithm iterations and the population capacity determine the duration of each optimization, which generally has the defect of poor effectiveness. In literature [2], the fitness function of the genetic algorithm is embedded with the simulated annealing algorithm, which is difficult to solve and will definitely increase significantly. At the time of each iteration, the inter-population immigration operator used in the multi-population genetic algorithm in [3] has little effect, and does not consider the requirements of smoothness and stability in actual USV navigation to set limits on steering and speed

The heuristic binary initialization coding process adopted in literature [1] is complicated and redundant, adding, deleting, and repairing operations have little effect, and it is difficult to model and measure economy, smoothness, and security as evaluation factors, and the simple simulation case designed cannot prove Algorithm effectiveness

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