Path Planning Method for Hoisting Objects of Cranes

Abstract

The invention provides a method for planning a path of a lift object for a crane. The method comprises the following steps of: projecting an obstacle on a working plane of the crane; performing polar radius-oriented processing on the projection and transforming a coordinate expression form of the obstacle into a polar coordinate expression form; analyzing the obstacle which is positioned on the path of the lift object to ensure that the lift object can pass through the path; and determining a lifting path according to a lifting principle. By the method for planning the path of the lift object for the crane, distances among obstacles can be calculated quickly and efficiently, the planned lifting path can be searched precisely, and the lifting safety and reliability of the lift object can be improved.

Description

technical field [0001] The invention relates to the field of crane hoisting, in particular to a method for path planning of crane hoisting objects. Background technique [0002] With the accelerated development of society, the rapid development of petroleum, chemical industry, metallurgy, electric power, ocean engineering, bridge construction, etc., hoisting engineering is also developing into complexity. At the hoisting site, the hoisting staff will first formulate a preliminary hoisting plan based on the scene of the hoisting site, then the ground hoisting instructor will correct the preliminary hoisting path based on the actual hoisting, and finally the ground hoisting instructor will complete the hoisting according to the revised hoisting path. The hoisting path in this hoisting scheme is formulated based on experience, there is no reasonable theoretical derivation mechanism, and the hoisting path planning is not based on hoisting principles. Therefore, the current hois...

AI Technical Summary

Problems solved by technology

Therefore, the current hoisting path planning has the following deficiencies: (1) The degree of execution is not high, and the impact of obstacles on the hoisting path in the scene is not fully considered; (2) The planned path is not necessarily the optimal path, and no path planning optimal search

[0005] This method assumes that the obstacle is a very simple object, and does not fully consider the obstacle height factor; this method searches for the shortest path, but in practice, it needs to search for the hoisting path according to the practical hoisting rules on the spot; this method is based on The neural network algorithm belongs to the intelligent algorithm, and the convergence and stability of this method are poor

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