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Unmanned crown block path planning method and system based on improved ant colony algorithm

An ant colony algorithm and path planning technology, applied in two-dimensional position/channel control, etc., can solve problems affecting factory production efficiency and economic benefits, collisions, losses, etc., to avoid local optimum, short path, improve The effect of production efficiency

Pending Publication Date: 2022-07-29
WISDRI WUHAN AUTOMATION
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AI Technical Summary

Problems solved by technology

If the path of the unmanned crane cannot reasonably avoid the locked area, collisions may occur during the automatic operation, resulting in heavy losses and serious safety hazards; the quality and length of the planned path directly determine the The efficiency of the car operation, thus affecting the production efficiency and economic benefits of the factory

Method used

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  • Unmanned crown block path planning method and system based on improved ant colony algorithm
  • Unmanned crown block path planning method and system based on improved ant colony algorithm
  • Unmanned crown block path planning method and system based on improved ant colony algorithm

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Embodiment 1

[0051] An unmanned aerial vehicle path planning method based on improved ant colony algorithm, such as figure 1 ,include:

[0052] S100. Set the warehouse information for the operation of the unmanned crane, including generating a grid map, determining the starting point and target point of the unmanned crane, and establishing an obstacle model;

[0053] In this implementation S100, the warehouse operated by the unmanned crane is modeled by the grid method, and a grid map of the warehouse is generated; the specific method of the grid method is to divide the actual physical environment into units, and divide them into units of equal size. The grid of the map is represented; the grid of the preset size is determined, so that the environmental information represented by the map is sufficient and sufficient, and the calculation efficiency of the subsequent path planning algorithm is guaranteed. Specifically, the warehouse environment is modeled by the grid method, and a grid map ...

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Abstract

An unmanned crown block path planning method based on an improved ant colony algorithm comprises the following steps: setting warehouse information, including generating a grid map, determining a starting point and a target point of an unmanned crown block, and establishing an obstacle model; performing optimal path calculation by adopting an improved ant colony algorithm according to the set warehouse information, and calculating an optimal operation path of the crown block after multiple iterations of the ant colony algorithm by taking the shortest path as an evaluation index; and issuing the optimal operation path obtained by calculation to the corresponding unmanned crown block, so that the unmanned crown block is planned to run according to the optimal path. According to the invention, map modeling is carried out by using obstacle information of a field warehouse, and path planning can be carried out according to a real-time physical environment; the improved ant colony algorithm is high in convergence speed, local optimum is avoided, meanwhile, path planning in a complex environment can be adapted, it is guaranteed that the unmanned crown block avoids a lock area when automatically working according to the optimal path in a warehouse, the path is shortest, the intelligent warehousing system operates stably, and the production efficiency is improved.

Description

technical field [0001] The invention relates to the field of path planning, in particular to a path planning method for an unmanned overhead crane based on an improved ant colony algorithm. Background technique [0002] At present, with the continuous development of industrial intelligent technology, the intelligent warehouse management system of unmanned cranes is widely used, which greatly reduces labor costs and improves production efficiency. Among them, the operation path of the unmanned crane has a prominent impact on the safety, stability and efficiency performance of the intelligent storage system. If the path of the unmanned crane cannot reasonably avoid the locked area, there may be collisions in the process of automatic operation, resulting in heavy losses and serious safety hazards; and the quality and length of the planned path directly determines the unmanned sky. The efficiency of the truck operation, thus affecting the production efficiency and economic bene...

Claims

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Application Information

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IPC IPC(8): G05D1/02
CPCG05D1/0217G05D1/0221G05D1/0274
Inventor 胡颖王傲能王胜勇卢家斌
Owner WISDRI WUHAN AUTOMATION
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