{"id":9843,"date":"2026-08-12T14:29:42","date_gmt":"2026-08-12T06:29:42","guid":{"rendered":"\/jase\/?post_type=tkuisotope&#038;p=9843"},"modified":"2026-08-17T23:39:15","modified_gmt":"2026-08-17T15:39:15","slug":"jase-202611-34-032","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=jase-202611-34-032","title":{"rendered":"Research on Automatic Tracking System of Dynamic Targets Based on UAV"},"content":{"rendered":"\n<div class=\"wp-block-tkuwpbs5-bs5-row row article-info\">\n<div class=\"wp-block-tkuwpbs5-bs5-column col-md-3 align-self-start\">\n<p><i class=\"fa fa-folder\" aria-hidden=\"true\"><\/i>&nbsp;<a href=\"\/jase\/?page_id=807\" data-type=\"page\" data-id=\"807\">2026<\/a><\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-tkuwpbs5-bs5-column col-md-3 align-self-start\">\n<p><i class=\"fa fa-folder-open\" aria-hidden=\"true\"><\/i>&nbsp;<a href=\"\/jase\/?page_id=9439\" data-type=\"page\" data-id=\"9439\">Volume 34<\/a><\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-tkuwpbs5-bs5-column col-md-6 align-self-start\">\n<div class=\"wp-block-tkuwpbs5-bs5-div dv_publish\" data-aos=\"normal\"><div class=\"wp-block-post-date\"><time datetime=\"2026-08-12T14:29:42+08:00\">2026-08-12<\/time><\/div><\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-tkuwpbs5-bs5-row row\">\n<div class=\"wp-block-tkuwpbs5-bs5-column col-md-5 align-self-start\">\n<div class=\"wp-block-tkuwpbs5-bs5-div au-ol\" data-aos=\"normal\">\n<p>Mengqi Wei and Qi Yang<a href=\"mailto:yangqi@sylu.edu.cn\"><i class=\"fa fa-envelope\"><\/i><\/a><\/p>\n\n\n\n<p style=\"font-size:14px\">School of Mechanical Engineering, Shenyang Ligong University, Shenyang 110159, China.<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-tkuwpbs5-bs5-div\" style=\"margin-top:var(--wp--preset--spacing--40)\" data-aos=\"normal\">\n<p>Received: June 03, 2026<br>Accepted:&nbsp;June 28, 2026<br>Publication Date:&nbsp;August 12, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-tkuwpbs5-bs5-column col-md-7 align-self-start clk=\u5716\u7247\"><img decoding=\"async\" src=\"\/jase\/wp-content\/uploads\/2026\/08\/34_032.jpg\" class=\"img-fluid img-fluid mx-auto d-block\" alt=\"\u4e0a\u50b3\u5716\u7247\">\n\n\n<p class=\"has-text-align-center\">SolidWorks 3D model of the multi-rotor UAV and&nbsp;two-axis direct-drive&nbsp;gimbal.&nbsp;<\/p>\n<\/div>\n<\/div>\n\n\n\n<p class=\"has-small-font-size\"><i class=\"fab fa-creative-commons\"><\/i>&nbsp;<strong>Copyright&nbsp;<\/strong>The Author(s). This is an open access article distributed under the terms of the&nbsp;<a rel=\"noreferrer noopener\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\" target=\"_blank\">Creative Commons Attribution&nbsp;License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n<p>Download Citation:\u00a0 <a href=\"\/jase\/wp-content\/uploads\/2026\/08\/V34.0032.txt\" data-type=\"attachment\" data-id=\"10219\" target=\"_blank\" rel=\"noreferrer noopener\">BibTeX <\/a>| <a rel=\"noreferrer noopener\" href=\"http:\/\/dx.doi.org\/10.6180\/jase.202611_34.032\" target=\"_blank\">http:\/\/dx.doi.org\/10.6180\/jase.202611_34.032<\/a>\u00a0\u00a0<\/p>\n\n\n\n<p class=\"btn btn-primary article-btn\"><a href=\"\/jase\/wp-content\/uploads\/2026\/08\/032_2026_1534_V34.pdf\" data-type=\"attachment\" data-id=\"9856\" target=\"_blank\" rel=\"noreferrer noopener\">Download PDF<\/a><\/p>\n\n\n\n<div style=\"height:24px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Aiming at the critical engineering pain points of visual tracking systems for small multi-rotor UAVs, including onboard payload redundancy, high control loop latency, and the inherent trade-off between response speed and steady-state accuracy in fixed-gain PID controllers, this paper presents a lightweight end-to-end edge vision two-axis gimbal automatic tracking system. To address the link hysteresis problem of traditional relay architectures, a middleware-free direct-connection architecture between OpenMV edge nodes and the Pixhawk flight controller is implemented, significantly reducing system hardware payload and communication latency. To mitigate integral windup and steady-state chattering caused by the mechanical backlash of micro servos, an incremental PID controller with visual front-end signal compensation is designed, which suppresses invalid oscillations through axis-differentiated dead-zone compensation. To overcome the poor adaptability of fixed proportional gains, nonlinear exponential adaptive logic is introduced to resolve the contradiction between rapid target convergence and overshoot suppression. To break through the limitation of flight controller low-level filtering on servo bandwidth, a software-hardware cross-mapping decoupling strategy is adopted to enhance the dynamic response performance of the system. Experimental results demonstrate that in high-frequency transverse reciprocating sinusoidal motion tests, the system can rapidly overcome instantaneous large deviations caused by target mutations; the step response settling time is reduced by 64% compared with the traditional relay architecture; and target reacquisition is completed within 300 ms after 600 ms of target occlusion. While strictly satisfying the onboard payload constraints of small UAVs, the system effectively improves the real-time performance and robustness of visual tracking systems.<\/p>\n\n\n\n<p><em>Keywords:&nbsp;Small Multi-Rotor Unmanned Aerial Vehicle (SUAV); Visual Servoing; Incremental PID; MAV Link Communication; End-to-End Control<\/em><\/p>\n\n\n\n<div style=\"height:2rem\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-tkuwpbs5-bs5-div ref_ol\" data-aos=\"normal\">\n<div class=\"container\">\n<div id=\"model-response-message-contentr_53180f64958e6cc2\" class=\"markdown markdown-main-panel md-content enable-luminous-fast-follows enable-updated-hr-color stronger\" dir=\"ltr\" aria-busy=\"false\" aria-live=\"polite\">\n<ol>\n<li data-path-to-node=\"0\">[1] D. Palossi, A. Loquercio, F. Conti, E. Flamand, D. Scaramuzza, and L. Benini, (2019) \u201cA 64-mW DNN-Based Visual Navigation Engine for Autonomous Nano-Drones\u201d IEEE Internet of Things Journal 6(5): 8357\u20138371. DOI: 10.1109\/JIOT.2019.2917066.<\/li>\n<li data-path-to-node=\"0\">[2] P. Corke. \u201cMobile Robot Vehicles\u201d. In: Robotics, Vision and Control: Fundamental Algorithms in MATLAB. Springer, 2017, 99\u2013124. DOI: 10.1007\/978-3-319-54413-7_4.<\/li>\n<li data-path-to-node=\"0\">[3] S. Tarbouriech and M. Turner, (2009) \u201cAnti-Windup Design: An Overview of Some Recent Advances and Open Problems\u201d IET Control Theory &amp; Applications 3(1): 1\u201319. DOI: 10.1049\/iet-cta:20070435.<\/li>\n<li data-path-to-node=\"0\">[4] M. Al Radi, M. N. AlMallahi, and A. S. Al-Sumaiti, (2024) \u201cProgress in Artificial Intelligence-Based Visual Servoing of Autonomous Unmanned Aerial Vehicles (UAVs)\u201d International Journal of Thermofluids: DOI: 10.1016\/j.ijft.2024.100590.<\/li>\n<li data-path-to-node=\"0\">[5] P. Warden and D. Situnayake. TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers. O&#8217;Reilly Media, 2019.<\/li>\n<li data-path-to-node=\"0\">[6] S. Peng, Y. Liu, Q. Huang, X. Zhou, and H. Bao. \u201cPVNet: Pixel-Wise Voting Network for 6DoF Pose Estimation\u201d. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2019, 4561\u20134570. DOI: 10.1109\/CVPR.2019.00469.<\/li>\n<li data-path-to-node=\"0\">[7] Z. Ning, H. Hu, X. Wang, L. Guo, S. Guo, G. Wang, and X. Gao, (2024) \u201cMobile Edge Computing and Machine Learning in the Internet of Unmanned Aerial Vehicles: A Survey\u201d ACM Computing Surveys 56(1): 1\u201331. DOI: 10.1145\/3604933.<\/li>\n<li data-path-to-node=\"0\">[8] Z. Li, D. Li, J. Yang, and H. Li. \u201cA Real-Time Monocular Vision-Aided Target Detection and Tracking for Micro UAV in GPS Denied Environment\u201d. In: Lecture Notes in Electrical Engineering. Springer, 2022. DOI: 10.1007\/978-981-15-8155-7_255.<\/li>\n<li data-path-to-node=\"0\">[9] S. Macenski, T. Foote, B. Gerkey, C. Lalancette, and W. Woodall, (2022) \u201cRobot Operating System 2: Design, Architecture, and Uses in the Wild\u201d Science Robotics 7(66): DOI: 10.1126\/scirobotics.abm6074.<\/li>\n<li data-path-to-node=\"0\">[10] P. McEnroe, S. Wang, and M. Liyanage, (2022) \u201cA Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges\u201d IEEE Internet of Things Journal 9(17): 15435\u201315459. DOI: 10.1109\/JIOT.2022.3176400.<\/li>\n<li data-path-to-node=\"0\">[11] L. Meier, P. Tanskanen, L. Heng, G. H. Lee, F. Fraundorfer, and M. Pollefeys, (2012) \u201cPIXHAWK: A Micro Aerial Vehicle Design for Autonomous Flight Using On-board Computer Vision\u201d Autonomous Robots 33(1): 21\u201339. DOI: 10.1007\/s10514-012-9281-4.<\/li>\n<li data-path-to-node=\"0\">[12] A. Koub\u00e2a, A. Allouch, M. Alajlan, Y. Javed, A. Belghith, and M. Khalgui, (2019) \u201cMicro Air Vehicle Link (MAVLink) in a Nutshell: A Survey\u201d IEEE Access 7: 87658\u201387680. DOI: 10.1109\/ACCESS.2019.2924410.<\/li>\n<li data-path-to-node=\"0\">[13] A. M. Nascimento, A. V. Brito, M. Saska, and T. P. Nascimento, (2026) \u201cA Review on Vision-Based Control for Multi-Rotor Aerial Vehicles\u201d Robotics and Autonomous Systems 198: DOI: 10.1016\/j.robot.2026.105366.<\/li>\n<li data-path-to-node=\"0\">[14] R. Szeliski. Computer Vision: Algorithms and Applications. 2nd. Springer, 2022. DOI: 10.1007\/978-3-030-34372-9.<\/li>\n<li data-path-to-node=\"0\">[15] F. Chaumette and S. Hutchinson, (2006) \u201cVisual Servo Control. I. Basic Approaches\u201d IEEE Robotics &amp; Automation Magazine 13(4): 82\u201390. DOI: 10.1109\/MRA.2006.250573.<\/li>\n<li data-path-to-node=\"0\">[16] B. Ekstrand, (2001) \u201cEquations of Motion for a Two-Axes Gimbal System\u201d IEEE Transactions on Aerospace and Electronic Systems 37(3): 1083\u20131091. DOI: 10.1109\/7.953259.<\/li>\n<li data-path-to-node=\"0\">[17] N. V. Phuong, N. T. Tuyen, N. D. Khanh, and N. N. Hung. \u201cDesigning a Robust Control System Based on Sliding Mode Control for Two-axis Gimbal Systems\u201d. In: 2024 Conference of Young Researchers in Electrical and Electronic Engineering (EICon). IEEE, 2024, 455\u2013458. DOI: 10.1109\/EICon61730.2024.10468229.<\/li>\n<li data-path-to-node=\"0\">[18] J. Kuang and M. Chen, (2024) \u201cAdaptive Sliding Mode Control for Trajectory Tracking of Quadrotor Unmanned Aerial Vehicles Under Input Saturation and Disturbances\u201d Drones 8(11): 614. DOI: 10.3390\/drones8110614.<\/li>\n<li data-path-to-node=\"0\">[19] I. L\u00f3pez-S\u00e1nchez and J. Moreno-Valenzuela, (2023) \u201cPID Control of Quadrotor UAVs: A Survey\u201d Annual Reviews in Control 56: 100900. DOI: 10.1016\/j.arcontrol.2023.100900.<\/li>\n<li data-path-to-node=\"0\">[20] A. Khalid, Z. Mushtaq, S. Arif, K. Zeb, M. A. Khan, and S. Bakshi, (2023) \u201cControl Schemes for Quadrotor UAV: Taxonomy and Survey\u201d ACM Computing Surveys: DOI: 10.1145\/3617652.<\/li>\n<li data-path-to-node=\"0\">[21] M.-Y. Ma, S.-E. Shen, and Y.-C. Huang, (2023) \u201cEnhancing UAV Visual Landing Recognition with YOLO&#8217;s Object Detection by Onboard Edge Computing\u201d Sensors 23(21): 8999. DOI: 10.3390\/s23218999.<\/li>\n<li data-path-to-node=\"0\">[22] C. Wang, D. Xu, Y. Zhu, R. Mart\u00edn-Mart\u00edn, C. Lu, L. Fei-Fei, and S. Savarese. \u201cDenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion\u201d. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2019, 3343\u20133352. DOI: 10.1109\/CVPR.2019.00346.<\/li>\n<li data-path-to-node=\"0\">[23] Z. Yu, Y. Zhang, B. Jiang, and C.-Y. Su. Fault-Tolerant Cooperative Control of Unmanned Aerial Vehicles. Springer Nature Singapore, 2023. DOI: 10.1007\/978-981-99-7661-4.<\/li>\n<li data-path-to-node=\"0\">[24] A. K. Kamath, Z. Zheng, and M. Feroskhan, (2025) \u201cDepth-Independent Augmented Dynamics Visual Servoing of Multirotors\u201d IEEE Transactions on Aerospace and Electronic Systems 61(2): 5444\u20135453. DOI: 10.1109\/TAES.2024.3496418.<\/li>\n<\/ol>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<p><\/p>\n","protected":false},"author":3,"template":"wp-custom-template-detail-4-aricles","meta":{"_uag_custom_page_level_css":""},"categories":[12,1682,6],"tags":[1714],"acf":[],"uagb_featured_image_src":[],"uagb_author_info":{"display_name":"\u6797\u923a\u6db5","author_link":"\/jase\/?author=3"},"uagb_comment_info":0,"uagb_excerpt":"&nbsp;Copyright&nbsp;The Author(s). This is an open access article distributed under the terms of the&nbsp;Creative Commons Attribution&nbsp;License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited. Download Citation:\u00a0 BibTeX | http:\/\/dx.doi.org\/10.6180\/jase.202611_34.032\u00a0\u00a0 Download PDF Aiming at the critical engineering pain points of visual tracking systems&hellip;","_links":{"self":[{"href":"\/jase\/index.php?rest_route=\/wp\/v2\/tkuisotope\/9843"}],"collection":[{"href":"\/jase\/index.php?rest_route=\/wp\/v2\/tkuisotope"}],"about":[{"href":"\/jase\/index.php?rest_route=\/wp\/v2\/types\/tkuisotope"}],"author":[{"embeddable":true,"href":"\/jase\/index.php?rest_route=\/wp\/v2\/users\/3"}],"wp:attachment":[{"href":"\/jase\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=9843"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"\/jase\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=9843"},{"taxonomy":"post_tag","embeddable":true,"href":"\/jase\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=9843"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}