Multi-robot path planning method based on multi-objective artificial bee colony algorithm

An artificial bee colony algorithm and path planning technology, applied in the direction of two-dimensional position/channel control, etc., can solve the conflict between path length, path safety and smoothness, cannot meet the needs of robot path planning, and is difficult to achieve simultaneous optimization And other issues

Inactive Publication Date: 2017-09-26
SHANGHAI UNIV
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AI Technical Summary

Problems solved by technology

However, in actual path planning problems, the path length, path security and smoothness are generally in conflict with each other, and it is difficult to achieve simultaneous optimization.
Only one path can be obtained at a time through traditional path planning methods, which cannot meet the path planning needs of robots in complex environments

Method used

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  • Multi-robot path planning method based on multi-objective artificial bee colony algorithm
  • Multi-robot path planning method based on multi-objective artificial bee colony algorithm
  • Multi-robot path planning method based on multi-objective artificial bee colony algorithm

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Embodiment Construction

[0050] The present invention will be further described below in conjunction with the accompanying drawings.

[0051] A kind of multi-robot path planning method based on the multi-objective artificial bee colony algorithm proposed by the present invention, such as figure 1 As shown, it specifically includes the following optimization steps:

[0052] Step 1: Environment Modeling

[0053] 1. Environmental modeling for path planning problems:

[0054] Such as figure 2 As shown, the path planning environment is set to a two-dimensional plane, and the global coordinate system O-XY of the environment map is established; Start is the starting point of the robot, and Target is the target point of the robot. The path of the robot can be expressed in the environment map as a set of starting point, target point and n path points passed in the middle: Path={Start,Step 1 ,Step 2 ,...,Step n ,Target}. Among them, set P={Step 1 ,Step 2 ,...,Step n} is the optimization goal of path ...

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Abstract

The invention provides a multi-robot path planning method based on a multi-objective artificial bee colony algorithm, which belongs to the technical field of path planning, and includes: environment modeling of the path planning problem, parameter initialization of the multi-objective artificial bee colony algorithm, and three kinds of bee iterative optimization. path and determine the non-inferior solution set, sort and retain the good path and output the optimal path set. The invention improves the standard artificial bee colony algorithm based on the concepts of Pareto dominance and non-dominated sorting of crowding distance, and proposes a multi-objective artificial bee colony algorithm suitable for solving multi-objective optimization problems. In the process of path planning, the algorithm can consider multiple performance indicators such as path length, smoothness and security, and a set of Pareto optimal paths can be obtained in one path planning. The path planning method proposed by the invention belongs to the meta-heuristic intelligent optimization method, which is different from the traditional single-objective path planning method, and can better adapt to the path planning task in the complex environment.

Description

technical field [0001] The invention relates to the technical field of path planning, in particular to a multi-robot path planning method based on a multi-objective artificial bee colony algorithm. Background technique [0002] Since the birth of robots, great changes have taken place in the way of life and production in human society. With the development of the demand for robots, people realize that when completing a complex task, compared with designing a single robot with complex functions, designing multiple robots with simple functions has many advantages in cost, efficiency, and robustness. Compared with a single robot, a multi-robot system has the advantages of higher efficiency, lower cost, high flexibility, and strong robustness. In multi-robot systems, mobile multi-robot systems are an important research direction. Designing mobile multi-robot systems with autonomous navigation is one of the key research issues. As the core of autonomous navigation technology, ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/02
Inventor 李敏窦连航李洋
Owner SHANGHAI UNIV
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