Path planning method for multiple mobile robots based on improved genetic algorithm

A technology for improving genetic algorithms and mobile robots is applied in the field of multi-mobile robot path planning based on improved genetic algorithms to achieve the effects of improving quality and efficiency and increasing population diversity.

Inactive Publication Date: 2017-08-25
ANHUI UNIVERSITY OF TECHNOLOGY AND SCIENCE
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Problems solved by technology

[0003] According to the deficiencies in the prior art above, the technical problem to be solved by the present invention is to propose a multi-mobile robot path planning method based on the improved genetic algorithm, to solve the technical deficiencies in the basic genetic algorithm for solving the robot path planning problem, and for mobile robots Path planning problem, the present invention takes the shortest path as the optimization goal, proposes the population initialization method of the artificial potential field method and the adaptive selection method of the population diversity degree to improve the population initialization step and the adaptive selection step in the genetic algorithm

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  • Path planning method for multiple mobile robots based on improved genetic algorithm
  • Path planning method for multiple mobile robots based on improved genetic algorithm
  • Path planning method for multiple mobile robots based on improved genetic algorithm

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[0038] Below with reference to accompanying drawing, through the description of embodiment, the specific embodiment of the present invention such as the shape of each component involved, structure, mutual position and connection relationship between each part, the effect of each part and working principle, manufacturing process And the method of operation and use, etc., are described in further detail to help those skilled in the art have a more complete, accurate and in-depth understanding of the inventive concepts and technical solutions of the present invention.

[0039] A multi-mobile robot path planning method based on an improved genetic algorithm, which is used to obtain optimal or near-optimal path planning and realize global optimization of mobile robots. The specific steps of the method include the following:

[0040] Step 1: Initialize the relevant parameters of the algorithm, such as the population size m, the termination evolution algebra T and the adjustment param...

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Abstract

The invention discloses a path planning method for multiple mobile robots based on an improved genetic algorithm, and belongs to the field of mobile robots. The path planning method mainly comprises the steps of initializing relevant parameters of the algorithm and initializing a population p(t); calculating a fitness value of each individual; judging whether a counter t meets termination conditions or not, if so, terminating the algorithm, enabling an optimal individual in the contemporary population to act as an optimal solution to output; if not, turning to the next step; selecting an individual which continues to perform evolution from the population p(t) according to a designed selection operating method; generating a random number R1 in a range of (0, 1), judging whether the random number R1 meets a crossover probability pc, and if so, turning to the next step; and if not, conducting other steps. The path planning method not only improves an acquired global optimal solution or near optimal solution for robot path planning, but also improves the convergence speed, and can be further popularized and applied to the fields such as production scheduling.

Description

technical field [0001] The invention belongs to the field of robot technology, relates to the path planning direction of mobile robots, is applicable to the optimization of path planning and can be further extended and referenced to fields such as job shop scheduling, and specifically relates to a multi-mobile robot path planning method based on an improved genetic algorithm. Background technique [0002] Path planning technology is an important part of the robot research field, and its development to a certain extent marks the level of robot intelligence, and the quality of the path planning method directly affects the path planning effect. At present, many experts and scholars at home and abroad are working on the research of path planning algorithms. The commonly used optimization algorithms mainly include artificial potential field method, immune algorithm, ant colony optimization algorithm, neural network, particle swarm optimization algorithm and genetic algorithm. Amo...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02G06N3/12
CPCG05D1/0219G05D1/0221G06N3/126
Inventor 王雷李明石鑫
Owner ANHUI UNIVERSITY OF TECHNOLOGY AND SCIENCE
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