{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T08:04:51Z","timestamp":1776326691570,"version":"3.50.1"},"reference-count":74,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,31]],"date-time":"2023-01-31T00:00:00Z","timestamp":1675123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"CEFET-RJ","award":["UIDB\/05757\/2020"],"award-info":[{"award-number":["UIDB\/05757\/2020"]}]},{"name":"CEFET-RJ","award":["UIDP\/05757\/2020"],"award-info":[{"award-number":["UIDP\/05757\/2020"]}]},{"name":"CEFET-RJ","award":["NORTE-06-3559-FSE-000188"],"award-info":[{"award-number":["NORTE-06-3559-FSE-000188"]}]},{"name":"CEFET-RJ","award":["NORTE 2020"],"award-info":[{"award-number":["NORTE 2020"]}]},{"name":"CAPES","award":["UIDB\/05757\/2020"],"award-info":[{"award-number":["UIDB\/05757\/2020"]}]},{"name":"CAPES","award":["UIDP\/05757\/2020"],"award-info":[{"award-number":["UIDP\/05757\/2020"]}]},{"name":"CAPES","award":["NORTE-06-3559-FSE-000188"],"award-info":[{"award-number":["NORTE-06-3559-FSE-000188"]}]},{"name":"CAPES","award":["NORTE 2020"],"award-info":[{"award-number":["NORTE 2020"]}]},{"name":"CNPq","award":["UIDB\/05757\/2020"],"award-info":[{"award-number":["UIDB\/05757\/2020"]}]},{"name":"CNPq","award":["UIDP\/05757\/2020"],"award-info":[{"award-number":["UIDP\/05757\/2020"]}]},{"name":"CNPq","award":["NORTE-06-3559-FSE-000188"],"award-info":[{"award-number":["NORTE-06-3559-FSE-000188"]}]},{"name":"CNPq","award":["NORTE 2020"],"award-info":[{"award-number":["NORTE 2020"]}]},{"name":"FAPERJ","award":["UIDB\/05757\/2020"],"award-info":[{"award-number":["UIDB\/05757\/2020"]}]},{"name":"FAPERJ","award":["UIDP\/05757\/2020"],"award-info":[{"award-number":["UIDP\/05757\/2020"]}]},{"name":"FAPERJ","award":["NORTE-06-3559-FSE-000188"],"award-info":[{"award-number":["NORTE-06-3559-FSE-000188"]}]},{"name":"FAPERJ","award":["NORTE 2020"],"award-info":[{"award-number":["NORTE 2020"]}]},{"name":"Research Centre in Digitalization and Intelligent Robotics (CeDRI)","award":["UIDB\/05757\/2020"],"award-info":[{"award-number":["UIDB\/05757\/2020"]}]},{"name":"Research Centre in Digitalization and Intelligent Robotics (CeDRI)","award":["UIDP\/05757\/2020"],"award-info":[{"award-number":["UIDP\/05757\/2020"]}]},{"name":"Research Centre in Digitalization and Intelligent Robotics (CeDRI)","award":["NORTE-06-3559-FSE-000188"],"award-info":[{"award-number":["NORTE-06-3559-FSE-000188"]}]},{"name":"Research Centre in Digitalization and Intelligent Robotics (CeDRI)","award":["NORTE 2020"],"award-info":[{"award-number":["NORTE 2020"]}]},{"name":"Instituto Polit\u00e9cnico de Bragan\u00e7a\u2013IPB","award":["UIDB\/05757\/2020"],"award-info":[{"award-number":["UIDB\/05757\/2020"]}]},{"name":"Instituto Polit\u00e9cnico de Bragan\u00e7a\u2013IPB","award":["UIDP\/05757\/2020"],"award-info":[{"award-number":["UIDP\/05757\/2020"]}]},{"name":"Instituto Polit\u00e9cnico de Bragan\u00e7a\u2013IPB","award":["NORTE-06-3559-FSE-000188"],"award-info":[{"award-number":["NORTE-06-3559-FSE-000188"]}]},{"name":"Instituto Polit\u00e9cnico de Bragan\u00e7a\u2013IPB","award":["NORTE 2020"],"award-info":[{"award-number":["NORTE 2020"]}]},{"name":"Foundation for Science and Technology","award":["UIDB\/05757\/2020"],"award-info":[{"award-number":["UIDB\/05757\/2020"]}]},{"name":"Foundation for Science and Technology","award":["UIDP\/05757\/2020"],"award-info":[{"award-number":["UIDP\/05757\/2020"]}]},{"name":"Foundation for Science and Technology","award":["NORTE-06-3559-FSE-000188"],"award-info":[{"award-number":["NORTE-06-3559-FSE-000188"]}]},{"name":"Foundation for Science and Technology","award":["NORTE 2020"],"award-info":[{"award-number":["NORTE 2020"]}]},{"name":"FCT\/MCTES (PIDDAC) to CeDRI","award":["UIDB\/05757\/2020"],"award-info":[{"award-number":["UIDB\/05757\/2020"]}]},{"name":"FCT\/MCTES (PIDDAC) to CeDRI","award":["UIDP\/05757\/2020"],"award-info":[{"award-number":["UIDP\/05757\/2020"]}]},{"name":"FCT\/MCTES (PIDDAC) to CeDRI","award":["NORTE-06-3559-FSE-000188"],"award-info":[{"award-number":["NORTE-06-3559-FSE-000188"]}]},{"name":"FCT\/MCTES (PIDDAC) to CeDRI","award":["NORTE 2020"],"award-info":[{"award-number":["NORTE 2020"]}]},{"name":"Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC)","award":["UIDB\/05757\/2020"],"award-info":[{"award-number":["UIDB\/05757\/2020"]}]},{"name":"Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC)","award":["UIDP\/05757\/2020"],"award-info":[{"award-number":["UIDP\/05757\/2020"]}]},{"name":"Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC)","award":["NORTE-06-3559-FSE-000188"],"award-info":[{"award-number":["NORTE-06-3559-FSE-000188"]}]},{"name":"Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC)","award":["NORTE 2020"],"award-info":[{"award-number":["NORTE 2020"]}]},{"name":"IPB, Portugal","award":["UIDB\/05757\/2020"],"award-info":[{"award-number":["UIDB\/05757\/2020"]}]},{"name":"IPB, Portugal","award":["UIDP\/05757\/2020"],"award-info":[{"award-number":["UIDP\/05757\/2020"]}]},{"name":"IPB, Portugal","award":["NORTE-06-3559-FSE-000188"],"award-info":[{"award-number":["NORTE-06-3559-FSE-000188"]}]},{"name":"IPB, Portugal","award":["NORTE 2020"],"award-info":[{"award-number":["NORTE 2020"]}]},{"name":"Project \u201cOleaChain: Compet\u00eancias para a sustentabilidade e inova\u00e7\u00e3o da cadeia de valor do olival tradicional no Norte Interior de Portugal\u201d","award":["UIDB\/05757\/2020"],"award-info":[{"award-number":["UIDB\/05757\/2020"]}]},{"name":"Project \u201cOleaChain: Compet\u00eancias para a sustentabilidade e inova\u00e7\u00e3o da cadeia de valor do olival tradicional no Norte Interior de Portugal\u201d","award":["UIDP\/05757\/2020"],"award-info":[{"award-number":["UIDP\/05757\/2020"]}]},{"name":"Project \u201cOleaChain: Compet\u00eancias para a sustentabilidade e inova\u00e7\u00e3o da cadeia de valor do olival tradicional no Norte Interior de Portugal\u201d","award":["NORTE-06-3559-FSE-000188"],"award-info":[{"award-number":["NORTE-06-3559-FSE-000188"]}]},{"name":"Project \u201cOleaChain: Compet\u00eancias para a sustentabilidade e inova\u00e7\u00e3o da cadeia de valor do olival tradicional no Norte Interior de Portugal\u201d","award":["NORTE 2020"],"award-info":[{"award-number":["NORTE 2020"]}]},{"name":"European Social Fund (ESF)","award":["UIDB\/05757\/2020"],"award-info":[{"award-number":["UIDB\/05757\/2020"]}]},{"name":"European Social Fund (ESF)","award":["UIDP\/05757\/2020"],"award-info":[{"award-number":["UIDP\/05757\/2020"]}]},{"name":"European Social Fund (ESF)","award":["NORTE-06-3559-FSE-000188"],"award-info":[{"award-number":["NORTE-06-3559-FSE-000188"]}]},{"name":"European Social Fund (ESF)","award":["NORTE 2020"],"award-info":[{"award-number":["NORTE 2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Agriculture"],"abstract":"<jats:p>Unmanned aerial vehicles (UAV) are a suitable solution for monitoring growing cultures due to the possibility of covering a large area and the necessity of periodic monitoring. In inspection and monitoring tasks, the UAV must find an optimal or near-optimal collision-free route given initial and target positions. In this sense, path-planning strategies are crucial, especially online path planning that can represent the robot\u2019s operational environment or for control purposes. Therefore, this paper proposes an online adaptive path-planning solution based on the fusion of rapidly exploring random trees (RRT) and deep reinforcement learning (DRL) algorithms applied to the generation and control of the UAV autonomous trajectory during an olive-growing fly traps inspection task. The main objective of this proposal is to provide a reliable route for the UAV to reach the inspection points in the tree space to capture an image of the trap autonomously, avoiding possible obstacles present in the environment. The proposed framework was tested in a simulated environment using Gazebo and ROS. The results showed that the proposed solution accomplished the trial for environments up to 300 m3 and with 10 dynamic objects.<\/jats:p>","DOI":"10.3390\/agriculture13020354","type":"journal-article","created":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T02:52:02Z","timestamp":1675219922000},"page":"354","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":66,"title":["Adaptive Path Planning for Fusing Rapidly Exploring Random Trees and Deep Reinforcement Learning in an Agriculture Dynamic Environment UAVs"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4037-7254","authenticated-orcid":false,"given":"Gabriel G. R. de","family":"Castro","sequence":"first","affiliation":[{"name":"Department of Electronics Engineering, Federal Center of Technological Education of Celso Suckow da Fonseca (CEFET\/RJ), Rio de Janeiro 20271-204, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4100-1494","authenticated-orcid":false,"given":"Guido S.","family":"Berger","sequence":"additional","affiliation":[{"name":"Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Polit\u00e9cnico de Bragan\u00e7a, Campus de Santa Apol\u00f3nia, 5300-253 Bragan\u00e7a, Portugal"},{"name":"Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, Campus de Santa Apol\u00f3nia, 5300-253 Bragan\u00e7a, Portugal"},{"name":"Engineering Department, School of Sciences and Technology, Universidade de Tr\u00e1s-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5930-2140","authenticated-orcid":false,"given":"Alvaro","family":"Cantieri","sequence":"additional","affiliation":[{"name":"Applied Robotics and Computation Laboratory\u2014LaRCA, Federal Institute of Paran\u00e1, Pinhais 3100, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0372-312X","authenticated-orcid":false,"given":"Marco","family":"Teixeira","sequence":"additional","affiliation":[{"name":"Coordena\u00e7\u00e3o do Curso de Engenharia de Software, COENS, Universidade Tecnol\u00f3gica Federal do Paran\u00e1\u2014UTFPR, Dois Vizinhos 85660-000, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7902-1207","authenticated-orcid":false,"given":"Jos\u00e9","family":"Lima","sequence":"additional","affiliation":[{"name":"Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Polit\u00e9cnico de Bragan\u00e7a, Campus de Santa Apol\u00f3nia, 5300-253 Bragan\u00e7a, Portugal"},{"name":"Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, Campus de Santa Apol\u00f3nia, 5300-253 Bragan\u00e7a, Portugal"},{"name":"INESC Technology and Science, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3803-2043","authenticated-orcid":false,"given":"Ana I.","family":"Pereira","sequence":"additional","affiliation":[{"name":"Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Polit\u00e9cnico de Bragan\u00e7a, Campus de Santa Apol\u00f3nia, 5300-253 Bragan\u00e7a, Portugal"},{"name":"Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, Campus de Santa Apol\u00f3nia, 5300-253 Bragan\u00e7a, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6916-700X","authenticated-orcid":false,"given":"Milena F.","family":"Pinto","sequence":"additional","affiliation":[{"name":"Department of Electronics Engineering, Federal Center of Technological Education of Celso Suckow da Fonseca (CEFET\/RJ), Rio de Janeiro 20271-204, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yaqot, M., and Menezes, B.C. (2021, January 10\u201312). Unmanned aerial vehicle (UAV) in precision agriculture: Business information technology towards farming as a service. Proceedings of the 2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), Sana\u2019a, Yemen.","DOI":"10.1109\/eSmarTA52612.2021.9515736"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Almalki, F.A., Soufiene, B.O., Alsamhi, S.H., and Sakli, H. (2021). A low-cost platform for environmental smart farming monitoring system based on IoT and UAVs. Sustainability, 13.","DOI":"10.3390\/su13115908"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1109\/TASE.2019.2914113","article-title":"Efficient routing for precedence-constrained package delivery for heterogeneous vehicles","volume":"17","author":"Bai","year":"2019","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Barrile, V., Simonetti, S., Citroni, R., Fotia, A., and Bilotta, G. (2022). Experimenting Agriculture 4.0 with Sensors: A Data Fusion Approach between Remote Sensing, UAVs and Self-Driving Tractors. Sensors, 22.","DOI":"10.3390\/s22207910"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Luque Vega, L.F., Lopez-Neri, E., Arellano-Muro, C.A., Gonzalez Jimenez, L.E., Ghommam, J., and Carrasco Navarro, R. (2020, January 18\u201321). UAV Flight Instructional Design for Industry 4.0 based on the Framework of Educational Mechatronics. Proceedings of the IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society, Singapore.","DOI":"10.1109\/IECON43393.2020.9255295"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"127546","DOI":"10.1016\/j.jclepro.2021.127546","article-title":"Unmanned aerial vehicle and artificial intelligence revolutionizing efficient and precision sustainable forest management","volume":"311","author":"Liu","year":"2021","journal-title":"J. Clean. Prod."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"103107","DOI":"10.1016\/j.jnca.2021.103107","article-title":"A survey on the role of Internet of Things for adopting and promoting Agriculture 4.0","volume":"187","author":"Raj","year":"2021","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Lyu, X., Li, X., Dang, D., Dou, H., Wang, K., and Lou, A. (2022). Unmanned Aerial Vehicle (UAV) Remote Sensing in Grassland Ecosystem Monitoring: A Systematic Review. Remote Sens., 14.","DOI":"10.3390\/rs14051096"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1002\/agj2.20595","article-title":"Review on unmanned aerial vehicles, remote sensors, imagery processing, and their applications in agriculture","volume":"113","author":"Olson","year":"2021","journal-title":"Agron. J."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Su, J., Zhu, X., Li, S., and Chen, W.H. (2022). AI meets UAVs: A survey on AI empowered UAV perception systems for precision agriculture. Neurocomputing.","DOI":"10.1016\/j.neucom.2022.11.020"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"48572","DOI":"10.1109\/ACCESS.2019.2909530","article-title":"Unmanned aerial vehicles (UAVs): A survey on civil applications and key research challenges","volume":"7","author":"Shakhatreh","year":"2019","journal-title":"IEEE Access"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1066","DOI":"10.1016\/j.culher.2016.06.006","article-title":"Drones over Mediterranean landscapes. The potential of small UAV\u2019s (drones) for site detection and heritage management in archaeological survey projects: A case study from Le Pianelle in the Tappino Valley, Molise (Italy)","volume":"22","author":"Stek","year":"2016","journal-title":"J. Cult. Herit."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2786","DOI":"10.1017\/S026357472100196X","article-title":"Hybrid methodology based on computational vision and sensor fusion for assisting autonomous UAV on offshore messenger cable transfer operation","volume":"40","author":"Ramos","year":"2022","journal-title":"Robotica"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Silva, M.F., Lu\u00eds Lima, J., Reis, L.P., Sanfeliu, A., and Tardioli, D. (2019, January 20\u201322). Coverage Path Planning Optimization for Slopes and Dams Inspection. Proceedings of the Robot 2019: Fourth Iberian Robotics Conference, Porto, Portugal.","DOI":"10.1007\/978-3-030-35990-4_55"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Alsalam, B.H.Y., Morton, K., Campbell, D., and Gonzalez, F. (2017, January 4\u201311). Autonomous UAV with vision based on-board decision making for remote sensing and precision agriculture. Proceedings of the 2017 IEEE Aerospace Conference, Big Sky, MT, USA.","DOI":"10.1109\/AERO.2017.7943593"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1007\/s11119-012-9274-5","article-title":"The application of small unmanned aerial systems for precision agriculture: A review","volume":"13","author":"Zhang","year":"2012","journal-title":"Precis. Agric."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"100103","DOI":"10.1016\/j.atech.2022.100103","article-title":"Trends in Remote Sensing Technologies in Olive Cultivation","volume":"3","author":"Anastasiou","year":"2022","journal-title":"Smart Agric. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"100019","DOI":"10.1016\/j.srs.2021.100019","article-title":"UAV & satellite synergies for optical remote sensing applications: A literature review","volume":"3","author":"Corpetti","year":"2021","journal-title":"Sci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Parasuraman, K., Anandan, U., and Anbarasan, A. (2021, January 4\u20136). IoT Based Smart Agriculture Automation in Artificial Intelligence. Proceedings of the 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), Tirunelveli, India.","DOI":"10.1109\/ICICV50876.2021.9388578"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Anwarul, S., Misra, T., and Srivastava, D. (2022, January 13\u201314). An IoT & AI-assisted Framework for Agriculture Automation. Proceedings of the 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), Noida, India.","DOI":"10.1109\/ICRITO56286.2022.9964567"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4557","DOI":"10.1007\/s11831-022-09761-4","article-title":"Machine Learning for Smart Agriculture and Precision Farming: Towards Making the Fields Talk","volume":"29","author":"Shaikh","year":"2022","journal-title":"Arch. Comput. Methods Eng."},{"key":"ref_22","first-page":"134","article-title":"A review on motion planning and obstacle avoidance approaches in dynamic environments","volume":"4","author":"Kamil","year":"2015","journal-title":"Adv. Robot. Autom."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.1016\/j.asoc.2009.02.014","article-title":"Path planning for autonomous mobile robot navigation with ant colony optimization and fuzzy cost function evaluation","volume":"9","author":"Garcia","year":"2009","journal-title":"Appl. Soft Comput."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"156787","DOI":"10.1109\/ACCESS.2019.2949835","article-title":"Hybrid path planning algorithm based on membrane pseudo-bacterial potential field for autonomous mobile robots","volume":"7","author":"Picos","year":"2019","journal-title":"IEEE Access"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1016\/j.amc.2013.07.022","article-title":"Dynamic robot path planning using an enhanced simulated annealing approach","volume":"222","author":"Miao","year":"2013","journal-title":"Appl. Math. Comput."},{"key":"ref_26","unstructured":"L\u00f3pez-Villalta, M.C. (1999). Olive Pest and Disease Management, International Olive Oil Council."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1080\/09670874.2013.851428","article-title":"The use of trap captures to forecast infestation by the olive fly, Bactrocera oleae (Rossi) (Diptera: Tephritidae), in traditional olive groves in north-eastern Portugal","volume":"59","author":"Torres","year":"2013","journal-title":"Int. J. Pest Manag."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1109\/MM.2021.3134744","article-title":"Challenges and Opportunities for Autonomous Micro-UAVs in Precision Agriculture","volume":"42","author":"Liu","year":"2022","journal-title":"IEEE Micro"},{"key":"ref_29","unstructured":"Koenig, N., and Howard, A. (October, January 28). Design and use paradigms for gazebo, an open-source multi-robot simulator. Proceedings of the 2004 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)(IEEE Cat. No. 04CH37566), Sendai, Japan."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Roy Choudhury, M., Das, S., Christopher, J., Apan, A., Chapman, S., Menzies, N.W., and Dang, Y.P. (2021). Improving Biomass and Grain Yield Prediction of Wheat Genotypes on Sodic Soil Using Integrated High-Resolution Multispectral, Hyperspectral, 3D Point Cloud, and Machine Learning Techniques. Remote Sens., 13.","DOI":"10.3390\/rs13173482"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1135","DOI":"10.1007\/s13762-021-03801-5","article-title":"UAV-based remote sensing in plant stress imagine using high-resolution thermal sensor for digital agriculture practices: A meta-review","volume":"20","author":"Awais","year":"2023","journal-title":"Int. J. Environ. Sci. Technol."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Velusamy, P., Rajendran, S., Mahendran, R.K., Naseer, S., Shafiq, M., and Choi, J.G. (2022). Unmanned Aerial Vehicles (UAV) in Precision Agriculture: Applications and Challenges. Energies, 15.","DOI":"10.3390\/en15010217"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Gao, T., Gao, Z., Sun, B., Qin, P., Li, Y., and Yan, Z. (2022). An Integrated Method for Estimating Forest-Canopy Closure Based on UAV LiDAR Data. Remote Sens., 14.","DOI":"10.3390\/rs14174317"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Roma, E., and Catania, P. (2022). Precision Oliviculture: Research Topics, Challenges, and Opportunities\u2014A Review. Remote Sens., 14.","DOI":"10.3390\/rs14071668"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Morales Rodriguez, P.A., Cano Cano, E., Villena, J., and Lopez Perales, J.A. (2022). A Comparison between Conventional Sprayers and New UAV Sprayers: A Study Case of Vineyards and Olives in Extremadura (Spain). Agronomy, 12.","DOI":"10.3390\/agronomy12061307"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Di Nisio, A., Adamo, F., Acciani, G., and Attivissimo, F. (2020). Fast Detection of Olive Trees Affected by Xylella Fastidiosa from UAVs Using Multispectral Imaging. Sensors, 20.","DOI":"10.3390\/s20174915"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Rahman, M.F.F., Fan, S., Zhang, Y., and Chen, L. (2021). A Comparative Study on Application of Unmanned Aerial Vehicle Systems in Agriculture. Agriculture, 11.","DOI":"10.3390\/agriculture11010022"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Anifantis, A.S., Camposeo, S., Vivaldi, G.A., Santoro, F., and Pascuzzi, S. (2019). Comparison of UAV Photogrammetry and 3D Modeling Techniques with Other Currently Used Methods for Estimation of the Tree Row Volume of a Super-High-Density Olive Orchard. Agriculture, 9.","DOI":"10.3390\/agriculture9110233"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"107148","DOI":"10.1016\/j.comnet.2020.107148","article-title":"A compilation of UAV applications for precision agriculture","volume":"172","author":"Sarigiannidis","year":"2020","journal-title":"Comput. Netw."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"105457","DOI":"10.1016\/j.compag.2020.105457","article-title":"Agroview: Cloud-based application to process, analyze and visualize UAV-collected data for precision agriculture applications utilizing artificial intelligence","volume":"174","author":"Ampatzidis","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2703","DOI":"10.1007\/s13762-021-03195-4","article-title":"Assessment of optimal flying height and timing using high-resolution unmanned aerial vehicle images in precision agriculture","volume":"19","author":"Awais","year":"2022","journal-title":"Int. J. Environ. Sci. Technol."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Lytridis, C., Kaburlasos, V.G., Pachidis, T., Manios, M., Vrochidou, E., Kalampokas, T., and Chatzistamatis, S. (2021). An Overview of Cooperative Robotics in Agriculture. Agronomy, 11.","DOI":"10.3390\/agronomy11091818"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Delavarpour, N., Koparan, C., Nowatzki, J., Bajwa, S., and Sun, X. (2021). A Technical Study on UAV Characteristics for Precision Agriculture Applications and Associated Practical Challenges. Remote Sens., 13.","DOI":"10.3390\/rs13061204"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1007\/s11370-018-0260-2","article-title":"Neural network-based approaches for mobile robot navigation in static and moving obstacles environments","volume":"12","author":"Singh","year":"2019","journal-title":"Intell. Serv. Robot."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"102142","DOI":"10.1016\/j.ijinfomgt.2020.102142","article-title":"On the training of a neural network for online path planning with offline path planning algorithms","volume":"57","author":"Sung","year":"2021","journal-title":"Int. J. Inf. Manag."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"63","DOI":"10.3389\/fnbot.2020.00063","article-title":"The path planning of mobile robot by neural networks and hierarchical reinforcement learning","volume":"14","author":"Yu","year":"2020","journal-title":"Front. Neurorobotics"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1109\/LWC.2020.2973624","article-title":"Remote UAV online path planning via neural network-based opportunistic control","volume":"9","author":"Shiri","year":"2020","journal-title":"IEEE Wirel. Commun. Lett."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Yang, K., and Sukkarieh, S. (2008, January 27\u201329). Real-time continuous curvature path planning of UAVs in cluttered environments. Proceedings of the 2008 5th International Symposium on Mechatronics and Its Applications, Amman, Jordan.","DOI":"10.1109\/ISMA.2008.4648836"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1007\/s11633-013-0750-9","article-title":"Path planning in complex 3D environments using a probabilistic roadmap method","volume":"10","author":"Yan","year":"2013","journal-title":"Int. J. Autom. Comput."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Debnath, S.K., Omar, R., Bagchi, S., Sabudin, E.N., Kandar, M.H.A.S., Foysol, K., and Chakraborty, T.K. Different Cell Decomposition Path Planning Methods for Unmanned Air Vehicles\u2014A Review. Proceedings of the 11th National Technical Seminar on Unmanned System Technology 2019, Lecture Notes in Electrical Engineering.","DOI":"10.1007\/978-981-15-5281-6_8"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Sch\u00f8ler, F., la Cour-Harbo, A., and Bisgaard, M. (2011, January 8\u201311). Generating configuration spaces and visibility graphs from a geometric workspace for uav path planning. Proceedings of the AIAA Guidance, Navigation, and Control Conference, Portland, OR, USA.","DOI":"10.2514\/6.2011-6416"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/BF01386390","article-title":"A note on two problems in connexion with graphs","volume":"1","author":"Dijkstra","year":"1959","journal-title":"Numer. Math."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1109\/TSSC.1968.300136","article-title":"A formal basis for the heuristic determination of minimum cost paths","volume":"4","author":"Hart","year":"1968","journal-title":"IEEE Trans. Syst. Sci. Cybern."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Carsten, J., Ferguson, D., and Stentz, A. (2006, January 9\u201315). 3D field D: Improved path planning and replanning in three dimensions. Proceedings of the 2006 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Beijing, China.","DOI":"10.1109\/IROS.2006.282516"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Juneja, S.S., Saraswat, P., Singh, K., Sharma, J., Majumdar, R., and Chowdhary, S. (2019, January 4\u20136). Travelling salesman problem optimization using genetic algorithm. Proceedings of the 2019 Amity International Conference on Artificial Intelligence (AICAI), Dubai, United Arab Emirates.","DOI":"10.1109\/AICAI.2019.8701246"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"548","DOI":"10.2514\/1.53889","article-title":"Neural network-based trajectory optimization for unmanned aerial vehicles","volume":"35","author":"Horn","year":"2012","journal-title":"J. Guid. Control Dyn."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Horn, J., Geiger, B., and Schmidt, E. (2009, January 10\u201313). Use of neural network approximation in multiple-unmanned aerial vehicle trajectory optimization. Proceedings of the AIAA Guidance, Navigation, and Control Conference, Chicago, IL, USA.","DOI":"10.2514\/6.2009-6103"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.knosys.2018.05.033","article-title":"Survey on computational-intelligence-based UAV path planning","volume":"158","author":"Zhao","year":"2018","journal-title":"Knowl. -Based Syst."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Chen, X., and Zhang, J. (2013, January 26\u201327). The three-dimension path planning of UAV based on improved artificial potential field in dynamic environment. Proceedings of the 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, Hangzhou, China.","DOI":"10.1109\/IHMSC.2013.181"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1080\/00207720903470155","article-title":"Path optimisation of a mobile robot using an artificial neural network controller","volume":"42","author":"Singh","year":"2011","journal-title":"Int. J. Syst. Sci."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1569","DOI":"10.1007\/s00521-013-1393-z","article-title":"Automatic navigation of mobile robots in unknown environments","volume":"24","author":"Motlagh","year":"2014","journal-title":"Neural Comput. Appl."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Qureshi, A.H., Simeonov, A., Bency, M.J., and Yip, M.C. (2019, January 20\u201324). Motion planning networks. Proceedings of the 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada.","DOI":"10.1109\/ICRA.2019.8793889"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1007\/s10846-019-01073-3","article-title":"Towards real-time path planning through deep reinforcement learning for a UAV in dynamic environments","volume":"98","author":"Yan","year":"2020","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1016\/j.cja.2020.05.011","article-title":"UAV navigation in high dynamic environments: A deep reinforcement learning approach","volume":"34","author":"Tong","year":"2021","journal-title":"Chin. J. Aeronaut."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Smolyanskiy, N., Kamenev, A., Smith, J., and Birchfield, S. (2017, January 24\u201328). Toward low-flying autonomous MAV trail navigation using deep neural networks for environmental awareness. Proceedings of the 2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada.","DOI":"10.1109\/IROS.2017.8206285"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1007\/s10846-013-9901-z","article-title":"Geometric reinforcement learning for path planning of UAVs","volume":"77","author":"Zhang","year":"2015","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_67","first-page":"578159","article-title":"Dynamic path planning of unknown environment based on deep reinforcement learning","volume":"2018","author":"Lei","year":"2018","journal-title":"J. Robot."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1109\/TNN.2005.860885","article-title":"Tuning the structure and parameters of a neural network by using hybrid Taguchi-genetic algorithm","volume":"17","author":"Tsai","year":"2006","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.neucom.2019.05.001","article-title":"TDPP-Net: Achieving three-dimensional path planning via a deep neural network architecture","volume":"357","author":"Wu","year":"2019","journal-title":"Neurocomputing"},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Andrade, F.A., Guedes, I.P., Carvalho, G.F., Zachi, A.R., Haddad, D.B., Almeida, L.F., de Melo, A.G., and Pinto, M.F. (2021). Unmanned Aerial Vehicles Motion Control with Fuzzy Tuning of Cascaded-PID Gains. Machines, 10.","DOI":"10.3390\/machines10010012"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1049\/trit.2020.0024","article-title":"Multi-robot path planning based on a deep reinforcement learning DQN algorithm","volume":"5","author":"Yang","year":"2020","journal-title":"CAAI Trans. Intell. Technol."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"1522","DOI":"10.1109\/TASE.2018.2877499","article-title":"Coarse-to-Fine UAV Target Tracking with Deep Reinforcement Learning","volume":"16","author":"Zhang","year":"2019","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_73","first-page":"85","article-title":"Dynamic Path Planning Based on Neural Networks for Aerial Inspection","volume":"34","author":"Pinto","year":"2022","journal-title":"J. Control. Autom. Electr. Syst."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Berger, G.S., Teixeira, M., Cantieri, A., Lima, J., Pereira, A.I., Valente, A., Castro, G.G.R.D., and Pinto, M.F. (2023). Cooperative Heterogeneous Robots for Autonomous Insects Trap Monitoring System in a Precision Agriculture Scenario. Agriculture, 13.","DOI":"10.3390\/agriculture13020239"}],"container-title":["Agriculture"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2077-0472\/13\/2\/354\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:20:17Z","timestamp":1760120417000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2077-0472\/13\/2\/354"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,31]]},"references-count":74,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["agriculture13020354"],"URL":"https:\/\/doi.org\/10.3390\/agriculture13020354","relation":{},"ISSN":["2077-0472"],"issn-type":[{"value":"2077-0472","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,31]]}}}