协作机械臂末端执行器的快速定位算法

doi:10.3969/j.issn.1000-1158.2021.07.01

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摘要针对传统的协作机械臂末端执行器即时定位效果差的问题,采用AprilTag标签定位,提出一种基于几何学提取ROI的快速定位算法。该算法对宏观尺寸目标采用下采样方法搜索有效局部范围,建立几何约束提取边缘像素点,加速目标识别速度。为了验证所提出算法的有效性,设计了机械臂末端执行器的视觉定位系统实验。实验结果表明:该算法的角点检测相对误差平均值低于0.1pixel,且检测速度提高至40帧/s,实现了对机械臂末端的快速定位。

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	喻靖
	江文松
	罗哉
	杨力
	周根明

关键词 ：计量学, 末端执行器, 协作机械臂, 快速定位, 单目视觉, AprilTag识别, 下采样, 图像处理

Abstract：Aiming at the poor real-time positioning effect of the traditional cooperative manipulator end-effector, AprilTag tag positioning was adopted to propose a fast positioning algorithm based on geometry to extract ROI. The algorithm uses a downsampling method to search the effective local range for macro-size targets, and establishes geometric constraints to extract edge pixels to accelerate the speed of target recognition. In order to verify the effectiveness of the proposed algorithm, a visual positioning system experiment is designed for the end-effector of the manipulator. The experimental results show that the speed of the proposed algorithm is improved to 40frame/s under the average relative error of corner detection is lower than 0.1pixel. Therefore, the proposeed algorithm realizes the rapid positioning of the end of the manipulator.

Key words： metrology end-effector cooperative vision fast positioning monocular vision AprilTag recognition downsampling image processing

收稿日期: 2020-06-19 发布日期: 2021-07-15

PACS:	TB92
	TP241.2

基金资助:国家重点研发计划(2017YFF0206306,2018YFF01012006,2019YFB2004900);国家自然科学基金(51675499,51927811);浙江省自然科学基金(LQ20E050016);浙江省重点研发计划(2020C01096)

通讯作者: 江文松(1988-),安徽怀宁人,中国计量大学计量测试工程学院副教授,主要从事工业视觉测量技术研究。Email: jwensong@cjlu.edu.cn E-mail: jwensong@cjlu.edu.cn

作者简介: 喻靖(1996-),江西新余人,中国计量大学测试计量与工程学院硕士研究生,主要研究方向为机器视觉的移动测量机器人关键技术。Email: 1420402566@qq.com

引用本文:

喻靖,江文松,罗哉,杨力,周根明. 协作机械臂末端执行器的快速定位算法[J]. 计量学报, 2021, 42(7): 833-839.
YU Jing,JIANG Wen-song,LUO Zai,YANG Li,ZHOU Gen-ming. Fast Positioning Algorithm for End-effector of Cooperative Manipulator. Acta Metrologica Sinica, 2021, 42(7): 833-839.

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［1］杨孟军. 基于视觉SLAM的移动机器人闭环检测研究［D］. 广州: 广东工业大学, 2018.
［2］李秀智, 李尚宇, 贾松敏, 等. 实时的移动机器人语义地图构建系统［J］. 仪器仪表学报, 2017, 38(11): 2769-2778.
Li X Z, Li S Y, Jia S M, et al. Real-time mobile robot semantic map construction system［J］. Chinese Journal of Scientific Instrument, 2017, 38(11): 2769-2778.
［3］李亚茹. 基于机器视觉的大尺寸板材测量方法研究［D］. 天津: 天津工业大学, 2019.
［4］郭子健. 基于视觉传感器的移动机器人位姿估计［D］. 北京: 北方工业大学, 2010.
［5］Hinkel H, Zipay J J, Strube M, et al. Technology Development of Automated Rendezvous and Docking/Capture Sensors and Docking Mechanism for the Asteroid Redirect Crewed Mission［C］// IEEE Aerospace Conference. Beijing, China, 2016.
［6］温卓漫. 复杂场景下合作靶标的准确快速识别与定位［D］. 长春: 中国科学院长春光学精密机械与物理研究所, 2017.
［7］汤元会, 张黎辉. 一种基于图像处理的交通运动目标快速检测方法［J］. 计量学报, 2019, 40(6A): 94-98.
Tang Y H, Zhang L H. A fast detection method of traffic moving targets based on image processing［J］. Acta Metrologica Sinica, 2019, 40(6A): 94-98.
［8］李爽. 基于视觉的室内定位算法研究［D］. 哈尔滨: 哈尔滨工程大学, 2017.
［9］何珍, 楼佩煌, 钱晓明, 等. 多目视觉与激光组合导航AGV精确定位技术研究［J］. 仪器仪表学报, 2017, 38(11): 2830-2838.
He Z, Lou P H, Qian X M, et al. Research on AGV precise positioning technology of multi-eye vision and laser combined navigation［J］. Chinese Journal of Scientific Instrument, 2017, 38(11): 2830-2838.
［10］叶波. 基于四旋翼平台的融合单目视觉与惯性传感的里程计方法研究［D］. 杭州: 浙江大学, 2017.
［11］雷金周. 基于单目视觉的目标位姿测量与机器人定位技术研究［D］. 南京: 南京航空航天大学, 2018.
［12］Olson E. AprilTag: A robust and flexible visual fiducial system［C］// International Conference on Robotics and Automation, Shanghai, China, 2011.
［13］刘虹, 王文祥. 三维扫描测头精确跟踪的摄影测量方法［J］. 计算机应用, 2017, 37(7): 2057-2061.
Liu H, Wang W X. Photogrammetry method for precise tracking of three-dimensional scanning probe［J］. computer application, 2017, 37(7): 2057-2061.
［14］贾配洋, 彭晓东, 沈菲菲, 等. 基于Apriltags改进算法的无人机移动目标识别与跟踪［J］. 电子设计工程, 2017, 25(17): 31-35.
Jia P Y, Peng X D, Shen F F, et al. UAV moving target recognition and tracking based on improved apriltags algorithm［J］. Electronic Design Engineering, 2017, 25(17): 31-35.
［15］汪惠芬, 张坚, 徐骏善. 基于改进的Apriltag标签的移动机器人视觉定位方法［P］. CN 108827316, 2018.
［16］Duan H Y, Zhang Y M, Sheng W. Image Digital Zoom Based Single Target Apriltag Recognition Algorithm in Large Scale Changes on the Distance［C］// The 1st International Conference on Industrial Artificial Intelligence (IAI), Shenyang, China, 2019.
［17］Ren R N, Chen G Z, Wang M L, et al. A Real-time Monocular Tracking Method for Low-Cost Mobile Robot［C］// International Conference on Information and Automation (ICIA), Wuyishan, China, 2018.
［18］Wang J, Olson E. Apriltag2: Efcient and robust ducial detection［C］// International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, 2016.
［19］Chow C K, Kaneko T. Automatic boundary detection of the left ventricle from cineangiograms［J］. Computers and Biomedical Research an International Journal, 1972, 5(4): 388-410.
［20］Thomas H C, Charles E L, Ronald L R, et al. Introduction to Algorithms［M］. Commonwealth of Massachusetts: The MIT Press, 2009.
［21］Karl P. On Lines and Planes of Closest Fit to Systems of Points in Space［M］. London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 1901.
［22］Lepetit V, Moreno-noguer F, Fua P, et al. Epnp: An Accurate O(n) Solution to the PnP Problem［J］. International Journal of Computer Vision, 2009, 81(2): 155-166.
［23］Xu W F, Liang B, Cheng L I, et al. Measurement and Planning Approach of Space Robot for Capturing Non-cooperative Target: Measurement and Planning Approach of Space Robot for Capturing Non-cooperative Target［J］. Robot, 2010, 32(1): 61-69.