[1]朱齐丹,李小铜,郑天昊.舰载机位姿实时视觉测量算法研究[J].智能系统学报,2021,16(6):1045-1055.[doi:10.11992/tis.202103014]
ZHU Qidan,LI Xiaotong,ZHENG Tianhao.Research on real-time vision measurement algorithm of shipborne aircraft pose[J].CAAI Transactions on Intelligent Systems,2021,16(6):1045-1055.[doi:10.11992/tis.202103014]
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ZHU Qidan,LI Xiaotong,ZHENG Tianhao.Research on real-time vision measurement algorithm of shipborne aircraft pose[J].CAAI Transactions on Intelligent Systems,2021,16(6):1045-1055.[doi:10.11992/tis.202103014]
舰载机位姿实时视觉测量算法研究
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
16
期数:
2021年第6期
页码:
1045-1055
栏目:
学术论文—机器感知与模式识别
出版日期:
2021-11-05
- Title:
- Research on real-time vision measurement algorithm of shipborne aircraft pose
- Keywords:
- machine vision; shipborne aircraft pose; deep learning; target detection; edge extraction; wireframe matching; GPU acceleration; target segmentation
- 分类号:
- TP391.4
- 摘要:
- 舰载机位姿实时检测对于甲板上的舰载机的运动控制、轨迹规划与防撞等具有重要意义。传统的舰载机调度主要依靠人工判断舰载机位置与航向角进行调度，传统方法不能得出准确数据，还易因为操作员的疏忽与疲劳发生碰撞事故。针对该问题，提出了舰载机位姿实时视觉测量算法。基于YOLO-V4(you only look once version 4)网络以及Canny边缘提取算法对舰载机进行识别分割。创新性地提出一种线框模板匹配算法，通过计算舰载机边缘轮廓与线框模板的匹配度获取最佳位姿。通过并行化与GPU(graphics processing unit)加速，使其满足实时性要求，并在1∶70与1∶14的实物模拟环境中完成测试。结果表明，该算法识别率在95%以上，位置精度在8 mm以内，姿态精度在0.7°以内，速度可达8 Hz。
- Abstract:
- Real-time detection of carrier aircraft pose is of great significance to the movement control, trajectory planning, and collision avoidance of carrier-based aircraft on deck. The traditional scheduling of carrier aircraft mainly relies on the manual judgment of the position and heading angle of the carrier-based aircraft. Traditional methods fail to obtain accurate data and readily cause collisions because of operator negligence and fatigue. Therefore, a real-time visual measurement algorithm for the pose of carrier aircraft is proposed. First, the carrier aircraft is identified and segmented based on the you only look once version 4 (YOLO-V4) network and the Canny edge extraction algorithm. Then, an innovative algorithm for wireframe template matching is proposed, and the best pose is obtained by calculating the matching degree between the contour of the carrier aircraft and the wireframe template. The algorithm meets the real-time requirements through parallelization and graphics processing unit acceleration, and the test is completed in the 1:70 and 1:14 physical simulation environments. The results show that the recognition rate of this algorithm is >95%, the accuracy is within 0.7° and 8 mm, and the speed can reach 8 Hz.
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备注/Memo
收稿日期:2021-03-09。
基金项目:国家自然科学基金项目(61803116)；船舶态势智能感知系统研制项目(MC-201920-X01)
作者简介:朱齐丹，教授，博士生导师，中国自动化学会应用委员会委员，国家绕月探测科学应用专家委员会专家，主要研究方向为智能机器人技术及应用、智能控制系统设计、图像处理与模式识别。主持国家自然科学基金项目、国防973项目、工信部高技木船舶专项项目、科工局国防基础研究重点项目、科技部国际合作项目、海军预研、科研、型号项目等50余项。获国家科技进步二等奖1项、国防科技进步一等奖3项、军队科技进步一等奖1项、黑龙江省科技进步二等奖3项。获发明专利授权20项、软件著作权5项，出版专著4部，发表学术论文200余篇;李小铜，硕士研究生，主要研究方向为图像处理、机器视觉、深度学习;郑天昊，硕士研究生，主要研究方向为计算机视觉、深度学习、机械臂、并行编程
通讯作者:朱齐丹.E-mail:zhuqidan@hrbeu.edu.cn
更新日期/Last Update:
2021-12-25