A path planning method for unmanned equipment considering energy supply

Abstract

The invention discloses a path planning method for unmanned equipment considering energy supply, which is applied in the field of unmanned equipment, where the mobile task of an unmanned equipment is multiple target nodes, and there are multiple energy supply sites between each target node In the present invention, by establishing a task update sliding window for the unmanned equipment, the energy supply node to be selected is added to the path planning topology, and through the sliding window and iteratively calculating the path, the movement path of the unmanned equipment is in Under the premise of meeting the energy constraints, the path cost and computational overhead should be reduced as much as possible.

Description

technical field [0001] The invention belongs to the field of unmanned equipment, and in particular relates to a planning technology for moving paths when unmanned equipment performs tasks. Background technique [0002] Unmanned equipment movement path planning is a part of unmanned equipment mission planning, that is, when the unmanned equipment is performing a task, it finds a movement path from the task start node to the task termination node under the constraints of various constraints. And the found path needs to meet certain task requirements, or meet certain established indicators. Unmanned equipment path planning is the basis for realizing unmanned equipment mobile tasks. For example, in military reconnaissance, considering the requirements of concealment and real-time performance, it is usually necessary for unmanned equipment to move between multiple given search target points to obtain the information of the search area and transmit it to the console in real time....

AI Technical Summary

Problems solved by technology

Since this method mainly uses heuristic algorithms and optimized mathematical models to plan UAV paths, when there are many search target points, the number of moving paths will increase exponentially, the established mathematical model is complex, and the algorithm convergence speed is relatively slow Slow, it is difficult to meet the real-time requirements

Moreover, most path planning algorithms seldom consider the energy supply of unmanned equipment when they are applied to the path planning of unmanned equipment. Requirements for on-duty and automatic continuous work

In addition, the traditional path planning algorithm also has the disadvantage of high algorithm complexity due to the need for large-scale mathematical modeling and planning of the global path.

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