{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T06:52:17Z","timestamp":1778223137986,"version":"3.51.4"},"reference-count":34,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,12,5]],"date-time":"2022-12-05T00:00:00Z","timestamp":1670198400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of Tennessee Knoxville","award":["000629"],"award-info":[{"award-number":["000629"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>The decline of natural pollinators necessitates the development of novel pollination technologies. In this work, we propose a drone-enabled autonomous pollination system (APS) that consists of five primary modules: environment sensing, flower perception, path planning, flight control, and pollination mechanisms. These modules are highly dependent upon each other, with each module relying on inputs from the other modules. In this paper, we focus on approaches to the flower perception, path planning, and flight control modules. First, we briefly introduce a flower perception method from our previous work to create a map of flower locations. With a map of flowers, APS path planning is defined as a variant of the Travelling Salesman Problem (TSP). Two path planning approaches are compared based on mixed-integer programming (MIP) and genetic algorithms (GA), respectively. The GA approach is chosen as the superior approach due to the vast computational savings with negligible loss of optimality. To accurately follow the generated path for pollination, we develop a convex optimization approach to the quadrotor flight control problem (QFCP). This approach solves two convex problems. The first problem is a convexified three degree-of-freedom QFCP. The solution to this problem is used as an initial guess to the second convex problem, which is a linearized six degree-of-freedom QFCP. It is found that changing the objective of the second convex problem to minimize the deviation from the initial guess provides improved physical feasibility and solutions similar to a general-purpose optimizer. The path planning and flight control approaches are then tested within a model predictive control (MPC) framework where significant computational savings and embedded adjustments to uncertainty are observed. Coupling the two modules together provides a simple demonstration of how the entire APS will operate in practice.<\/jats:p>","DOI":"10.3390\/robotics11060144","type":"journal-article","created":{"date-parts":[[2022,12,5]],"date-time":"2022-12-05T09:46:45Z","timestamp":1670233605000},"page":"144","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Perception, Path Planning, and Flight Control for a Drone-Enabled Autonomous Pollination System"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0389-7736","authenticated-orcid":false,"given":"Chapel Reid","family":"Rice","sequence":"first","affiliation":[{"name":"Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Spencer Thomas","family":"McDonald","sequence":"additional","affiliation":[{"name":"Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02141, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9579-9403","authenticated-orcid":false,"given":"Yang","family":"Shi","sequence":"additional","affiliation":[{"name":"Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3926-6239","authenticated-orcid":false,"given":"Hao","family":"Gan","sequence":"additional","affiliation":[{"name":"Department of Biosystems Engineering and Soil Science, University of Tennessee Institute of Agriculture, Knoxville, TN 37996, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9420-4789","authenticated-orcid":false,"given":"Won Suk","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Chen","sequence":"additional","affiliation":[{"name":"Zhejiang Laboratory, Hangzhou 311100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8979-9765","authenticated-orcid":false,"given":"Zhenbo","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1255957","DOI":"10.1126\/science.1255957","article-title":"Bee declines driven by combined stress from parasites, pesticides, and lack of flowers","volume":"347","author":"Goulson","year":"2015","journal-title":"Science"},{"key":"ref_2","first-page":"62","article-title":"A vision feedback robotic docking crane system with application to vanilla pollination","volume":"7","author":"Shaneyfelt","year":"2013","journal-title":"Autom. Control"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ohi, N., Lassak, K., Watson, R., Strader, J., Du, Y., Yang, C., Hedrick, G., Nguyen, J., Harper, S., and Reynolds, D. (2018, January 1\u20135). Design of an autonomous precision pollination robot. Proceedings of the 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain.","DOI":"10.1109\/IROS.2018.8594444"},{"key":"ref_4","unstructured":"Ahn, H.S., Dayoub, F., Popovic, M., MacDonald, B., Siegwart, R., and Sa, I. (2018). An overview of perception methods for horticultural robots: From pollination to harvest. arXiv."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1038\/scientificamerican0313-60","article-title":"Flight of the Robobees","volume":"308","author":"Wood","year":"2013","journal-title":"Sci. Am."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1038\/s41586-019-1322-0","article-title":"Untethered flight of an insect-sized flapping-wing microscale aerial vehicle","volume":"570","author":"Jafferis","year":"2019","journal-title":"Nature"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.chempr.2017.01.012","article-title":"Sticky solution provides grip for the first robotic pollinator","volume":"2","author":"Amador","year":"2017","journal-title":"Chem"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1002\/rob.21861","article-title":"Autonomous pollination of individual kiwifruit flowers: Toward a robotic kiwifruit pollinator","volume":"37","author":"Williams","year":"2019","journal-title":"J. Field Robot."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"106641","DOI":"10.1016\/j.compag.2021.106641","article-title":"Real-time detection of kiwifruit flower and bud simultaneously in orchard using YOLOv4 for robotic pollination","volume":"193","author":"Li","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"107114","DOI":"10.1016\/j.compag.2022.107114","article-title":"Design of a lightweight robotic arm for kiwifruit pollination","volume":"198","author":"Li","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Mazinani, M., Dehghani, M., Zarafshan, P., Etezadi, H., Vahdati, K., and Chegini, G. (2021, January 17\u201319). Design and Manufacture of an Aerial Pollinator Robot for Walnut Trees. Proceedings of the 2021 9th RSI International Conference on Robotics and Mechatronics (ICRoM), Tehran, Iran.","DOI":"10.1109\/ICRoM54204.2021.9663500"},{"key":"ref_12","first-page":"1137","article-title":"Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks","volume":"39","author":"Ren","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_13","unstructured":"Smith, G.S. (1995, January 22\u201326). Digital Orthophotography and GIS. Proceedings of the 1995 ESRI User Conference, Palm Springs, CA, USA."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Chen, Y., Lee, W.S., Gan, H., Peres, N., Fraisse, C., Zhang, Y., and He, Y. (2019). Strawberry yield prediction based on a deep neural network using high-resolution aerial orthoimages. Remote Sens., 11.","DOI":"10.3390\/rs11131584"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.trc.2015.03.005","article-title":"The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery","volume":"54","author":"Murray","year":"2015","journal-title":"Transp. Res. Part C"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2377","DOI":"10.1109\/LRA.2021.3110316","article-title":"External Forces Resilient Safe Motion Planning for Quadrotor","volume":"6","author":"Wu","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Khoufi, I., Laouiti, A., and Adjih, C. (2019). A Survey of Recent Extended Variants of the Traveling Salesman and Vehicle Routing Problems for Unmanned Aerial Vehicles. Drones, 3.","DOI":"10.3390\/drones3030066"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Conforti, M., Cornuejols, G., and Zambelli, G. (2014). Integer Programming, Springer.","DOI":"10.1007\/978-3-319-11008-0"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1145\/321043.321046","article-title":"Integer Programming Formulation of Traveling Salesman Problems","volume":"7","author":"Miller","year":"1960","journal-title":"J. ACM"},{"key":"ref_20","first-page":"339","article-title":"Genetic algorithms for the traveling salesman problem","volume":"63","year":"1996","journal-title":"Ann. Oper. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1002\/rob.20414","article-title":"Survey of Advances in Guidance, Navigation, and Control of Unmanned Rotorcraft Systems","volume":"29","author":"Kendoul","year":"2012","journal-title":"J. Field Robot."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Boyd, S., and Vandenberghe, L. (2004). Convex Optimization, Cambridge University Press.","DOI":"10.1017\/CBO9780511804441"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Domahidi, A., Chu, E., and Boyd, S. (2013, January 17\u201319). ECOS: An SOCP Solver for Embedded Systems. Proceedings of the 2013 European Control Conference (ECC), Zurich, Switzerland.","DOI":"10.23919\/ECC.2013.6669541"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"105756","DOI":"10.1016\/j.ast.2020.105756","article-title":"Convex relaxation for optimal rendezvous of unmanned aerial and ground vehicles","volume":"99","author":"Wang","year":"2020","journal-title":"Aerosp. Sci. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2603","DOI":"10.2514\/1.G002150","article-title":"Constrained trajectory optimization for planetary entry via sequential convex programming","volume":"40","author":"Wang","year":"2017","journal-title":"J. Guid. Control Dyn."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Mueller, M., and D\u2019Andrea, R. (2013, January 17\u201319). A model predictive controller for quadrocopter state interception. Proceedings of the 2013 European Control Conference (ECC), Zurich, Switzerland.","DOI":"10.23919\/ECC.2013.6669415"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Augugliaro, F., Schoellig, A., and D\u2019Andrea, R. (2012, January 7\u201312). Generation of collision-free trajectories for a quadrocopter fleet: A sequential convex programming approach. Proceedings of the 2012 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Vilamoura-Algarve, Portugal.","DOI":"10.1109\/IROS.2012.6385823"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Chen, Y., Cutler, M., and How, J.P. (2015, January 26\u201330). Decoupled Multiagen Path Planning via Incremental Sequential Convex Programming. Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA.","DOI":"10.1109\/ICRA.2015.7140034"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Camacho, E.F., and Bordons, C. (1999). Model Predictive Control, Springer.","DOI":"10.1007\/978-1-4471-3398-8"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1002\/asjc.1758","article-title":"Nonlinear and Adaptive Intelligent Control Techniques for Quadrotor UAV\u2014A Survey","volume":"21","author":"Mo","year":"2019","journal-title":"Asian J. Control"},{"key":"ref_31","unstructured":"MathWorks Help Center (2022, February 02). Traveling Salesman Problem: Solver-Based. Available online: https:\/\/www.mathworks.com\/help\/optim\/ug\/travelling-salesman-problem.html."},{"key":"ref_32","unstructured":"Kirk, J. (2022, February 14). Fixed Endpoints Open Traveling Salesman Problem Genetic Algorithm in Matlab. Available online: http:\/\/freesourcecode.net\/matlabprojects\/61164\/fixed-endpoints-open-traveling-salesman-problem\u2014genetic-algorithm-in-matlab."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s10846-005-9015-3","article-title":"Time-optimal Control of a Hovering Quad-Rotor Helicopter","volume":"45","author":"Lai","year":"2006","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2558904","article-title":"GPOPS-II: A MATLAB Software for Solving Multiple-Phase Optimal Control Problems Using hp-Adaptive Gaussian Quadrature Collocation Methods and Sparse Nonlinear Programming","volume":"41","author":"Patterson","year":"2014","journal-title":"ACM Trans. Math. Softw."}],"container-title":["Robotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-6581\/11\/6\/144\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:34:33Z","timestamp":1760146473000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-6581\/11\/6\/144"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,5]]},"references-count":34,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["robotics11060144"],"URL":"https:\/\/doi.org\/10.3390\/robotics11060144","relation":{},"ISSN":["2218-6581"],"issn-type":[{"value":"2218-6581","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,5]]}}}