A multi-uav regional coverage and target tracking method with improved swarm control

CN117128969BActive Publication Date: 2026-07-07NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
Filing Date
2023-08-17
Publication Date
2026-07-07

AI Technical Summary

Technical Problem

Existing multi-UAV systems have failed to effectively combine regional coverage and target tracking, resulting in insufficient attention being paid to optimizing regional coverage efficiency and target tracking performance.

Method used

An improved swarming method combining a probabilistic model based on ant colony algorithm and an anti-swarming algorithm is adopted. By combining a quadratic sliding mode controller and the swarming algorithm, a dual-mode control method for UAVs is designed. By constructing a simplified quadrotor UAV motion model and an information map communication mode among multiple UAVs, regional coverage and target tracking are achieved.

Benefits of technology

It achieves efficient coverage and rapid target tracking in a specific area. Simulation tests show that 12 drones can achieve more than 90% coverage after 50 seconds and form a stable local tracking formation for 3 randomly moving targets.

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Abstract

The application discloses a kind of multi-unmanned aerial vehicle area coverage and target tracking methods for improving swarm control, comprising the following steps: S1, in the inertial coordinate system, construct a simplified quadrotor unmanned aerial vehicle motion model, set unmanned aerial vehicle height unchanged when flying;S2, construct the communication mode between multiple unmanned aerial vehicles based on information map;S3, based on the evaluation quantity of velocity vector and Euclidean distance, construct target evaluation function;Based on target evaluation function, set the task switching mechanism of unmanned aerial vehicle, the task mode of unmanned aerial vehicle includes anti-swarm search mode and swarm tracking mode: in anti-swarm search mode, based on information map, select the optimal navigation point according to navigation point selection method;In swarm tracking mode, complete the target tracking of multiple unmanned aerial vehicles according to swarm tracking mode method.The application can realize the sensor network of unmanned aerial vehicle to meet the coverage task of specific area while tracking the target in the region.
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