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Robot welding path planning method based on firework particle swarm optimization algorithm

A technology of robot welding and particle swarm algorithm, which is applied in the direction of instruments, two-dimensional position/channel control, vehicle position/route/height control, etc., can solve the problems of slow algorithm convergence and time-consuming, and achieve optimal welding path and enhanced Population diversity, the effect of promoting optimization efficiency

Active Publication Date: 2019-03-29
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

Due to the unique explosion search mechanism of the fireworks algorithm, it has rich population diversity and strong global search capabilities, but at the same time, the algorithm converges slowly and is very time-consuming

Method used

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  • Robot welding path planning method based on firework particle swarm optimization algorithm
  • Robot welding path planning method based on firework particle swarm optimization algorithm
  • Robot welding path planning method based on firework particle swarm optimization algorithm

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Embodiment Construction

[0018] The method of the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0019] A robot welding path planning method based on fireworks particle swarm algorithm, such as figure 1 shown, including the following steps:

[0020] Step S1: Use the greedy algorithm to initialize all path solutions and all control parameters of the population.

[0021] The specific method is as follows:

[0022] Step S1.1: Randomly select a welding point as the position Pwelding where the welding robot is located, and add the sequence of visited welding points;

[0023] Step S1.2: Search all the welding points that have not joined the visited sequence, find the welding point Pnext closest to the current welding robot position Pwelding, add it to the visited sequence as the current welding robot position. Repeat the above search until all the solder joints are added to the visited sequence, and a preliminary optimized indi...

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Abstract

The invention provides a robot welding path planning method based on a firework particle swarm optimization algorithm, belonging to the technical field of robot welding control. The method comprises the following steps of: using a greedy algorithm to initialize all path solutions and parameters of the population; updating the speed and position of all population individuals according to the particle swarm operator; taking the individual of the particle swarm as a firework of the firework algorithm; generating sparks by modifying a blast operator and a Gaussian mutation operator; selecting firework populations by using an elite-roulette strategy; rebuilding the population by using a dual population strategy; and updating the individual historical optimal solution and the global optimal solution to obtain an optimal welding path. According to the robot welding path planning method based on the firework particle swarm optimization algorithm, the population diversity of the particle swarmis enhanced, information interaction among the firework algorithm individuals is achieved, and the optimal welding path is obtained by combining the particle swarm optimization algorithm with the firework algorithm, and the effectiveness and feasibility are high.

Description

technical field [0001] The invention relates to a robot welding path planning method, in particular to a robot welding path planning method based on fireworks particle swarm algorithm, which belongs to the technical field of robot welding control. Background technique [0002] In the field of equipment manufacturing, the use of robots for intelligent welding control is currently a widely used technical means. In order to improve the efficiency of robot welding, using computer control technology to optimize the design of the welding path is one of the important tasks of the technical personnel in this field. [0003] The Traveling Salesman Problem (TSP) is a typical non-deterministic polynomial difficulty problem in combinatorial optimization. Its essence is a problem of finding the shortest path planning, and it is also a very important problem in operations research and theoretical computer science. It is closely related to real life due to its wide application in the fiel...

Claims

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Application Information

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IPC IPC(8): G05D1/02G05B13/02
CPCG05B13/024G05B13/0265G05D1/0221
Inventor 赵清杰周欣瑜张长春
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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