Storage robot path planning method based on artificial bee colony-adaptive genetic algorithm

A genetic algorithm, artificial bee colony technology, applied in instruments, two-dimensional position/channel control, vehicle position/route/altitude control, etc. The effect of increasing consumption and improving quality

Pending Publication Date: 2021-12-07
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

The genetic algorithm has good parallelism, and it can evaluate multiple solutions in the search space, so that it presents good global search performance in the calculation and solution p

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  • Storage robot path planning method based on artificial bee colony-adaptive genetic algorithm
  • Storage robot path planning method based on artificial bee colony-adaptive genetic algorithm
  • Storage robot path planning method based on artificial bee colony-adaptive genetic algorithm

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Embodiment Construction

[0058] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0059] Wherein, the accompanying drawings are for illustrative purposes only, and represent only schematic diagrams, rather than physical drawings, and should...

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Abstract

The invention relates to a storage robot path planning method based on an artificial bee colony-adaptive genetic algorithm, and belongs to the field of path planing. The method comprises the steps of establishing a grid map according to storage environment and obstacle area position information; in allusion to the defects that the performance of a genetic algorithm depends on the quality of an initial population and selection, crossover and mutation operations of genetic operators, the convergence speed is low and local optimum is easily caused when robot path planning is solved, introducing an artificial bee colony algorithm bee nectar source searching mechanism to generate an initial population, so that the initial population quality of the genetic algorithm is improved; optimizing a path planning objective function, and taking a path length, a path turning node number and an energy consumption factor as evaluation indexes; and introducing self-adaptive crossover and mutation operators to improve the convergence speed of the algorithm. Compared with a traditional genetic algorithm, the improved genetic algorithm is greatly improved in the aspects of algorithm convergence speed, path smoothness and energy consumption.

Description

technical field [0001] The invention belongs to the field of robot path planning, and relates to a storage robot path planning method based on artificial bee colony-adaptive genetic algorithm. Background technique [0002] In recent years, the rise of e-commerce businesses led by Alibaba, JD.com and Pinduoduo has pushed the number of express packages in China to a new high. The explosive increase in the number of packages puts forward higher requirements on the operating efficiency of the warehousing logistics system, and the picking path planning of warehousing robots is one of the main factors affecting the efficiency of warehousing operations. [0003] The purpose of path planning is to find an optimal path from the starting point to the end point without collision in an environment with obstacles. In practical applications, more goals are often achieved, such as the shortest time required, the shortest path, and the least energy consumption. And so on, and these goals o...

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Application Information

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IPC IPC(8): G05D1/02
CPCG05D1/0223G05D1/0221G05D1/0276
Inventor 李艳生万勇匡衡阳张毅杨美美
Owner CHONGQING UNIV OF POSTS & TELECOMM
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