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Forklift global path planning method

A global path planning, forklift technology, applied in the direction of comprehensive factory control, comprehensive factory control, program control, etc., can solve the problems of long running time of the algorithm, local optimum, etc., to speed up the convergence speed, reduce the path length, and improve efficiency Effect

Active Publication Date: 2019-01-04
HEFEI UNIV OF TECH
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AI Technical Summary

Problems solved by technology

These algorithms are widely used in different fields, such as traveling salesman problem, power grid scheduling problem and path planning problem, but the unilaterally unimproved algorithm has different shortcomings such as long running time and easy to fall into local optimum.

Method used

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  • Forklift global path planning method

Examples

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Embodiment Construction

[0045] Such as figure 1 As shown, a forklift global path planning method, the method includes the following sequential steps:

[0046] (1) Establish a map model of the forklift working environment according to the actual working environment of the forklift combined with the grid method;

[0047] (2) Encode the path of the forklift and initialize N particles randomly;

[0048] (3) Establish a fitness function based on the forklift path length combined with the safety and smoothness of the forklift work;

[0049] (4) Generate a random number rand(0,1), judge whether the random number rand(0,1) meets the probability condition of using the elite reverse learning strategy, and update the global optimal particle according to the judgment result;

[0050] (5) Judging whether the convergence condition is met, if the judging result is yes, then output the optimal path, otherwise, return to step (4).

[0051]The step (2) specifically refers to: encoding the path connecting the starti...

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Abstract

The invention relates to a forklift global path planning method. The forklift global path planning method comprises the steps of establishing a cartographic model of a forklift working environment according to an actual working environment of a forklift and a grid method; encoding a forklift path and randomly initializing N particles; on the basis of the length of the forklift path, establishing afitness function according to safety degree and smoothness of forklift working; generating a random number rand (0, 1); judging whether the random number rand (0, 1) reaches a probability condition using an elitist reverse learning strategy or not; updating global optimal particles according to a judging result; judging whether a convergence condition is reached or not; and if the judging resultis that the convergence condition is reached, outputting an optimal path; and otherwise, returning to the step (4). The forklift global path planning method provided by the invention has the advantages that the convergence speed of particle swarm optimization is increased, the forklift global path planning efficiency is enhanced, and the planed path length is effectively reduced.

Description

technical field [0001] The invention relates to the technical field of AGV path planning, in particular to a global path planning method for forklifts. Background technique [0002] With the rapid development of the logistics industry, the demand for forklifts in warehouses is increasing day by day. However, the lockers that store objects will become obstacles in the actual work of forklifts. The core of solving this contradiction is actually to study the path planning problem of forklifts in the actual working environment. At present, experts and scholars at home and abroad have proposed different solutions to path planning problems, such as ant colony algorithm, particle swarm algorithm, simulated annealing algorithm and genetic algorithm. These algorithms have their own advantages and disadvantages, and some algorithms iterate quickly. But it is easy to fall into local optimum, and some algorithms are not easy to fall into local optimum, but their search efficiency is re...

Claims

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Application Information

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IPC IPC(8): G01C21/20G05B19/418
CPCG01C21/206G05B19/41895Y02P90/02
Inventor 肖本贤黄俊杰江志政张旭陈荣保
Owner HEFEI UNIV OF TECH
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