{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T17:27:57Z","timestamp":1791394077235,"version":"4.3.3"},"reference-count":32,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,6,14]],"date-time":"2020-06-14T00:00:00Z","timestamp":1592092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Unmanned aerial vehicle (UAV) has been used to assist agricultural production. Precision landing control of UAV is critical for application of it in some specific areas such as greenhouses or livestock\/poultry houses. For controlling UAV landing on a fixed or mobile apron\/platform accurately, this study proposed an automatic method and tested it under three scenarios: (1) UAV landing at high operating altitude based on the GPS signal of the mobile apron; (2) UAV landing at low operating altitude based on the image recognition on the mobile apron; and (3) UAV landing progress control based on the fixed landing device and image detection to achieve a stable landing action. To verify the effectiveness of the proposed control method, apron at both stationary and mobile (e.g., 3 km\/h moving speed) statuses were tested. Besides, a simulation was conducted for the UAV landing on a fixed apron by using a commercial poultry house as a model (135 L \u00d7 15 W \u00d7 3 H m). Results show that the average landing errors in high altitude and low altitude can be controlled within 6.78 cm and 13.29 cm, respectively. For the poultry house simulation, the landing errors were 6.22 \u00b1 2.59 cm, 6.79 \u00b1 3.26 cm, and 7.14 \u00b1 2.41cm at the running speed of 2 km\/h, 3 km\/h, and 4 km\/h, respectively. This study provides the basis for applying the UAV in agricultural facilities such as poultry or animal houses where requires a stricter landing control than open fields.<\/jats:p>","DOI":"10.3390\/s20123369","type":"journal-article","created":{"date-parts":[[2020,6,15]],"date-time":"2020-06-15T05:56:27Z","timestamp":1592200587000},"page":"3369","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Precision Landing Test and Simulation of the Agricultural UAV on Apron"],"prefix":"10.3390","volume":"20","author":[{"given":"Yangyang","family":"Guo","sequence":"first","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Northwest A&amp;F University, Yangling 712100, China"},{"name":"Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Yangling 712100, China"},{"name":"Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service, Yangling 712100, China"},{"name":"Department of Poultry Science, College of Agricultural and Environmental Sciences, University of Georgia, Athens, GA 30602, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaqian","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Northwest A&amp;F University, Yangling 712100, China"},{"name":"Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Yangling 712100, China"},{"name":"Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service, Yangling 712100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chang","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Northwest A&amp;F University, Yangling 712100, China"},{"name":"Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Yangling 712100, China"},{"name":"Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service, Yangling 712100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongting","family":"Xiong","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Northwest A&amp;F University, Yangling 712100, China"},{"name":"Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Yangling 712100, China"},{"name":"Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service, Yangling 712100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lilong","family":"Chai","sequence":"additional","affiliation":[{"name":"Department of Poultry Science, College of Agricultural and Environmental Sciences, University of Georgia, Athens, GA 30602, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongjian","family":"He","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Northwest A&amp;F University, Yangling 712100, China"},{"name":"Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Yangling 712100, China"},{"name":"Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service, Yangling 712100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,14]]},"reference":[{"key":"ref_1","first-page":"23","article-title":"Application of Unmanned Aerial Vehicle Technology in Modern Agriculture","volume":"6","author":"Zhang","year":"2016","journal-title":"Agric. Eng."},{"key":"ref_2","first-page":"1","article-title":"Key technology for remote sensing information acquisition based on micro UAV","volume":"30","author":"Wang","year":"2014","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_3","first-page":"247","article-title":"Status and Prospect of Agricultural Remote Sensing","volume":"46","author":"Shi","year":"2015","journal-title":"Trans. Chin. Soc. Agric. Mach."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1016\/j.compag.2015.09.001","article-title":"Field-based crop phenotyping: Multispectral aerial imaging for evaluation of winter wheat emergence and spring stand","volume":"118","author":"Sankaran","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.eja.2015.07.004","article-title":"Low-altitude, high-resolution aerial imaging systems for row and field crop phenotyping: A review","volume":"70","author":"Sankaran","year":"2015","journal-title":"Eur. J. Agron."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.compag.2018.05.034","article-title":"High-throughput field phenotyping in dry bean using small unmanned aerial vehicle based multispectral imagery","volume":"151","author":"Sankaran","year":"2018","journal-title":"Comput. Electron. Agric."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2235","DOI":"10.3389\/fpls.2017.02235","article-title":"Aerial images and convolutional neural network for cotton bloom detection","volume":"8","author":"Xu","year":"2018","journal-title":"Front. Plant. Sci."},{"key":"ref_8","first-page":"98","article-title":"Review of field-based phenotyping by unmanned aerial vehicle remote sensing platform","volume":"32","author":"Liu","year":"2016","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_9","first-page":"675","article-title":"Flight Attitudes and Spray Patterns of a Roll-Balanced Agricultural Unmanned Helicopter","volume":"29","author":"Bae","year":"2013","journal-title":"Appl. Eng. Agric."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.compag.2017.04.011","article-title":"An adaptive approach for UAV-based pesticide spraying in dynamic environments","volume":"138","author":"Freitas","year":"2017","journal-title":"Comput. Electron. Agric."},{"key":"ref_11","first-page":"53","article-title":"Current Status and Future Trends of Agricultural Aerial Spraying Technology in China","volume":"45","author":"Zhang","year":"2014","journal-title":"Trans. Chin. Soc. Agric. Mach."},{"key":"ref_12","first-page":"73","article-title":"Identification of diseased empty rice panicles based on Haar-like feature of UAV optical image","volume":"34","author":"Wang","year":"2018","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Albetis, J., Duthoit, S., Guttler, F., Jacquin, A., Goulard, M., Poilv\u00e9, H., F\u00e9ret, J.B., and Dedieu, G. (2017). Detection of Flavescence dor\u00e9e Grapevine Disease Using Unmanned Aerial Vehicle (UAV) Multispectral Imagery. Remote Sens., 9.","DOI":"10.3390\/rs9040308"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2017.07.007","article-title":"Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak","volume":"131","author":"Dash","year":"2017","journal-title":"ISPRS J. Photogramm."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Xuan-Mung, N., and Hong, S.-K. (2019). Improved Altitude Control Algorithm for Quadcopter Unmanned Aerial Vehicles. Appl. Sci., 9.","DOI":"10.3390\/app9102122"},{"key":"ref_16","first-page":"71","article-title":"Recognition Algorithm of the Apron for Unmanned Aerial Vehicle Based on Image Corner Points","volume":"08","author":"Wang","year":"2016","journal-title":"Laser J."},{"key":"ref_17","unstructured":"Olivares-Mendez, M.A., Mondrag\u00f3n, I., and Campoy, P. (2013, January 20\u201322). Autonomous Landing of an Unmanned Aerial Vehicle using Image-Based Fuzzy Control. Proceedings of the Second Workshop on Research, Development and Education on Unmanned Aerial Systems (RED-UAS 2013), Compiegne, France."},{"key":"ref_18","unstructured":"Amaral, T.G., Pires, V.F., and Crisostomo, M.M. (2005, January 28\u201330). Autonomous Landing of an Unmanned Aerial Vehicle. Proceedings of the International Conference on Computational Intelligence for Modelling, Control & Automation, & International Conference on Intelligent Agents, Web Technologies & Internet Commerce (CIMCA-IAWTIC\u201906), Vienna, Austria."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Bu, C., Ai, Y., and Du, H. (2016, January 10\u201312). Vision-based autonomous landing for rotorcraft unmanned aerial vehicle. Proceedings of the IEEE International Conference on Vehicular Electronics and Safety (ICVES), Beijing, China.","DOI":"10.1109\/ICVES.2016.7548174"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Kong, W., Zhou, D., Zhang, D., and Zhang, J. (2014, January 28\u201329). Vision-based autonomous landing system for unmanned aerial vehicle: A survey. Proceedings of the International Conference on Multisensor Fusion and Information Integration for Intelligent Systems (MFI), Beijing, China.","DOI":"10.1109\/MFI.2014.6997750"},{"key":"ref_21","unstructured":"Sharp, C.S., Shakernia, O., and Sastay, S.S. (2001, January 21\u201326). A vision system for landing an unmanned aerial vehicle. Proceedings of the ICRA IEEE International Conference on Robotics and Automation (Cat. No. 01CH37164), Seoul, Korea."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2250","DOI":"10.1016\/j.proeng.2012.06.271","article-title":"Vision Based Autonomous Landing of an Unmanned Aerial Vehicle","volume":"38","author":"Anitha","year":"2012","journal-title":"Procedia Eng."},{"key":"ref_23","first-page":"179","article-title":"Autonomous landing of unmanned helicopter based on landmark\u2019s geometrical feature","volume":"32","author":"Sun","year":"2012","journal-title":"J. Comput. Appl."},{"key":"ref_24","first-page":"2008","article-title":"Field scene recognition method for low-mall-slow unmanned aerial vehicle landing","volume":"37","author":"Ye","year":"2017","journal-title":"J. Comput. Appl."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Sudevan, V., Shukla, A., and Karki, H. (2017, January 18\u201321). Vision based Autonomous Landing of an Unmanned Aerial Vehicle on a Stationary Target. Proceedings of the 17th International Conference on Control, Automation and Systems (ICCAS), Ramada Plaza, Jeju, Korea.","DOI":"10.23919\/ICCAS.2017.8204466"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Hu, M., and Li, C.T. (2010, January 25). Application in real-time planning of UAV based on velocity vector field. Proceedings of the International Conference on Electrical and Control Engineering, Wuhan, China.","DOI":"10.1109\/iCECE.2010.1215"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Guanglei, M., Jinlong, G., Fengqin, S., and Feng, T. (June, January 31). UAV real-time path planning using dynamic RCS based on velocity vector field. Proceedings of the 26th Chinese Control and Decision Conference (2014 CCDC), Changsha, China.","DOI":"10.1109\/CCDC.2014.6852381"},{"key":"ref_28","unstructured":"Zhang, Z. (1999, January 20\u201327). Flexible Camera Calibration by Viewing a Plane from Unknown Orientations. Proceedings of the Seventh IEEE International Conference on Computer Vision, Kerkyra, Greece."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Olson, E. (2011, January 9\u201313). AprilTag: A robust and flexible visual fiducial system. Proceedings of the IEEE International Conference on Robotics and Automation, Shanghai, China.","DOI":"10.1109\/ICRA.2011.5979561"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"877","DOI":"10.13031\/trans.12982","article-title":"Mitigating particulate matter generations of a commercial cage-free henhouse","volume":"62","author":"Chai","year":"2019","journal-title":"Trans. ASABE"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Guo, Y., Chai, L., Aggrey, S.E., Oladeinde, A., Johnson, J., and Zock, G. (2020). A Machine Vision-Based Method for Monitoring Broiler Chicken Floor Distribution. Sensors, 20.","DOI":"10.3390\/s20113179"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"702","DOI":"10.3155\/1047-3289.60.6.702","article-title":"Assessment of long-term gas sampling design at two commercial manure-belt layer barns","volume":"60","author":"Chai","year":"2010","journal-title":"J. Air. Waste Manag."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/12\/3369\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:38:49Z","timestamp":1760175529000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/12\/3369"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,14]]},"references-count":32,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2020,6]]}},"alternative-id":["s20123369"],"URL":"https:\/\/doi.org\/10.3390\/s20123369","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,14]]}}}