Unmanned crane space collision avoidance strategy based on fuzzy decision inference

Abstract

The invention discloses an unmanned crane space collision avoidance strategy based on fuzzy decision inference. The unmanned crane space collision avoidance strategy includes the steps of firstly, determining the starting point and the ending point of a crane and a possible route; secondly, scanning the whole environment inside a workshop through lasers, and drawing a laser scanning result graph; calculating the space topological relations between the crane and entities such as devices and goods in all areas through the fuzzy inference and decision theory and a design algorithm when the route is selected, and judging whether the workshop is separated from the entities of equipment, goods and the like in each area of the workshop; replanning the route and executing the first step if the workshop is not separated from the entities of equipment, goods and the like in each area of the workshop; selecting and using the route and executing the hoisting task if the workshop is separated from the entities of equipment, goods and the like in each area of the workshop. The space topological relations between the crane on the assigned route and the other entities in the workshop are calculated through the fuzzy control theory and the fuzzy decision inference algorithm, the non-collision requirement of the hoisting task is met through supporting of the space topological relations, the detection means is provided for the feasibility of the route planning result of the unmanned crane, and reliability of the hoisting tank under the unmanned operation environment is improved.

Description

technical field [0001] The invention relates to the field of control, in particular to a design method of a space collision avoidance strategy for an unmanned crane based on fuzzy decision-making reasoning. Background technique [0002] Research on collision avoidance methods has widely appeared in path planning research for robots, ships, unmanned underwater autonomous vehicles, automatic guided vehicles, unmanned aerial vehicles, etc. At present, there are not too many studies on unmanned cranes, and most of them focus on the optimal path planning, and the collision avoidance problem is rarely mentioned. The existing research methods for collision avoidance in path planning mainly use sensors to perceive the machine itself and the external environment, judge the distance and angle information between itself and obstacles, and then change its own posture and direction of travel to avoid obstacles. This method is suitable for dynamic environments. On the predetermined track...

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Problems solved by technology

At present, there are not too many studies on unmanned cranes, and most of them f

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