Multi-UAV (unmanned aerial vehicle) cooperative searching method and system based on path planning and information fusion

Abstract

The invention provides a multi-UAV (unmanned aerial vehicle) cooperative searching method and system based on path planning and information fusion, and the method comprises a step of the real-time path planning: enabling each UAV to determine the movement and an observation object at a next moment according to current map information and an algorithm; a step of search map updating: updating a probability map and a certainty degree map according to an observation result; a step of information fusion: enabling each UAV to broadcast its own map information and receive the map information of otherUAVs, and calculating the real-time search map information; and a step of decision making: judging whether a target is located at a current position of the UAV or not according to the updated map information, and assisting the making of a decision according to the certainty degree map. The method can remarkably improve the search time, reduces the flight cost of task execution, improves the search accuracy, achieves the innovative fusion of real-time path planning and the information fusion, and enables a search mechanism to be more complete, efficient and reliable.

Description

technical field [0001] The present invention relates to a UAV cooperative search method, in particular to a multi-UAV cooperative search method based on path planning and information fusion, and to a multi-UAV cooperative search method based on path planning and information fusion Multi-UAV collaborative search system. Background technique [0002] Existing UAV target search technologies are mainly divided into two categories: effective coverage of search area and probability map mechanism based on Bayesian update. The UAV target search work related to the effective coverage of the search area aims to quickly search the entire area and reduce the overall uncertainty of the target area, regardless of the specific positioning of the target. The UAV target search technology based on Bayesian update and probability map mechanism models the target area as a separate rectangular unit, and generates a corresponding probability map according to the unit division of the map. The pro...

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Problems solved by technology

[0005] The above-mentioned existing technologies mainly have the following defects: first, the area coverage-based UAV target search technology ignores the UAV's own limitations (sensor performance and communication capabilities) and the dynamic changes of the environment, so it is difficult to efficiently target

Second, the probability map mechanism based on Bayesian update mainly has the following three problems: 1. Most of the related work does not study the movement model of the UAV, but simply stipulates that the UAV follows a fixed path or a random path. The method moves in the search area, an

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