Unmanned equipment path planning method giving consideration to energy supply

Abstract

The invention discloses an unmanned equipment path planning method giving consideration to energy supply, and is applied in the field of unmanned equipment. The movement task of one piece of unmannedequipment is multiple target nods, and the target nodes exist in a scene with a plurality of energy supply stations. According to the invention, one task updating sliding window is built for the unmanned equipment, and a candidate energy supply node is added to a path planning topology. Moreover, the method reduces the path cost and calculation expenditure as much as possible under the condition that the movement path of the unmanned equipment meets an energy constraint condition through the sliding window and a path iteration calculation mode.

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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