基于地标的轻量化无人机精准降落算法

doi:10.3778/j.issn.1002-8331.2101-0333

摘要/Abstract

摘要： 轻量化无人机的机载计算机通常计算性能较弱，很难满足无人机实现精准降落的需要。针对这一问题，提出了一种基于地标的轻量化精准降落算法，通过识别对比颜色和指定形状实现快速实时地检测着陆标识，图像处理流程简单快速且准确，通过相对位置计算在二维层面得到无人机对于降落地标的相对位置和方向，引导无人机精准降落，算法执行过程不需要考虑相机焦距。实际测试结果表明，在一些特定如无人机自主充电的应用场景，该算法过程简单，稳定性和降落精度相较于传统方法较高。

关键词: 无人机, 图像识别, 相对位置, 自主精准降落, 降落系统

Abstract: The on-board computer of lightweight UAVs is usually weak in computing performance, which is difficult to meet the needs of accurate landing. To solve this problem, a landmark-based lightweight and accurate landing algorithm is proposed. The landing logo can be detected quickly and in real time by identifying contrast colors and specified shapes. Image processing is simple rapid and accurate. Then by calculating the relative position of UAV and landing landmark in the two-dimensional plane, drone can get a landing location and direction. The algorithm execution process does not need to consider the camera focal length. The actual test results show that in some specific application scenarios, such as UAV autonomous charging, this algorithm has a simple process, higher stability and landing accuracy than the traditional method.

Key words: unmanned aerial vehicle（UAV）, image recognition, relative position, autonomous precision landing, landing system

原辉, 裴楚, 王帅, 李劲松, 姜敏, 仝家朋. 基于地标的轻量化无人机精准降落算法[J]. 计算机工程与应用, 2022, 58(17): 306-313.

YUAN Hui, PEI Chu, WANG Shuai, LI Jinsong, JIANG Min, TONG Jiapeng. Landmark-Based Lightweight UAV Accurate Landing Algorithm[J]. Computer Engineering and Applications, 2022, 58(17): 306-313.

参考文献

[1] GUO Y，GUO J，LIU C，et al.Precision landing test and simulation of the agricultural UAV on apron[J].Sensors，2020，20（12）：3369.
[2] 何昱，王彪，谷世宁，等.微小型四旋翼无人机自主着陆视觉系统研究[J].计算机测量与控制，2015（5）：1682-1685.
HE Y，WANG B，GU S N，et al.Vision system for autonomous landing of a micro four rotor UAV[J].Computer Measurement & Control，2015（5）：1682-1685.
[3] 罗哲.基于视觉的四旋翼无人机在特定平台上着陆系统研究[D].株洲：湖南工业大学，2015.
LUO Z.Research on landing system of quadrotor UAV on specific platform based on vision[D].Zhuzhou：Hunan University of Technology，2015.
[4] WUBBEN J，FABRA F，CALAFATE C T，et al.Accurate landing of unmanned aerial vehicles using ground pattern recognition[J].Electronics，2019，8（12）：5532.
[5] 樊珑.多旋翼无人机视觉引导降落研究[D].哈尔滨：哈尔滨工业大学，2016.
FAN L.Research on vision guided landing of multi rotor UAV[D].Harbin：Harbin Institute of Technology，2016.
[6] 张咪，赵勇，布树辉，等.基于阶层标识的无人机自主精准降落系统[J].航空学报，2018，39（10）：208-216.
ZHANG M，ZHAO Y，BU S H，et al.Multi-level marker based autonomous landing system for UAVs[J].Acta Aeronautica et Astronautica Sinica，2018，39（10）：208-216.
[7] 王龙.基于视觉辅助着陆的四旋翼飞行器设计及实现[D].武汉：武汉科技大学，2017.
WANG L.Design and implementation of four rotor aircraft based on vision assisted landing[D].Wuhan：Wuhan University of Science and Technology，2017.
[8] ZOTIN A.Fast algorithm of image enhancement based on multi-scale retinex[J].Procedia Computer Science，2018，131：6-14.
[9] KRUSE A W，ALENIN A S，VAUGHN I J，et al.Perceptually uniform color space for visualizing trivariate linear polarization imaging data[J].Optics Letters，2018，43（11）：2426-2429.
[10] 张金波.灰度图像的边缘检测算法研究[D].南京：东南大学，2019.
ZHANG J B.Research on edge detection algorithm of gray image[D].Nanjing：Southeast University，2019.
[11] WANG L，YANG Y，SHI J.Measurement of harvesting width of intelligent combine harvester by improved probabilistic Hough transform algorithm[J].Measurement，2020，151：107130.
[12] WANG J，WANG G，CHENG L.Texture extraction of wear particles based on improved random Hough transform and visual saliency[J].Engineering Failure Analysis，2020，109：104299.
[13] CAO X，LIU D，REN X.Detection method for auto guide vehicle’s walking deviation based on image thinning and Hough transform[J].Measurement and Control，2019，52（3/4）：252-261.
[14] 刘锦涛，吴文海，李静，等.无速度测量的四旋翼无人机移动目标跟踪控制[J].系统工程与电子技术，2017，39（2）：369-375.
LIU J T，WU W H，LI J，et al.Moving target tracking control of quadrotor UAVs without velocity measurement[J].Systems Engineering and Electronics，2017，39（2）：369-375.
[15] 王成，杨杰，姚辉，等.四旋翼无人机飞行控制算法综述[J].电光与控制，2018，25（12）：57-62.
WANG C，YANG J，YAO H，et al.An overview of flight control algorithms for quadrotors[J].Electronics Optics & Control，2018，25（12）：57-62.
[16] 葛畅，何振鹏，年哲，等.四旋翼无人机姿态测试平台设计及运动控制研究[J].机械设计，2019，36（S1）：136-140.
GE C，HE Z P，NIAN Z，et al.Design of attitude test platform and motion control of quadrotor UAV[J].Journal of Machine Design，2019，36（S1）：136-140.
[17] 陈菲雨，岳文斌，饶颖露，等.基于改进TLD算法的无人机自主精准降落[J].计算机工程与应用，2020，56（7）： 247-254.
CHEN F Y，YUN W B，RAO Y L，et al.Autonomous precision landing of drone based on improved TLD algorithm[J].Computer Engineering and Applications，2020，56（7）：247-254.