{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T17:54:00Z","timestamp":1768413240592,"version":"3.49.0"},"reference-count":52,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,10,28]],"date-time":"2023-10-28T00:00:00Z","timestamp":1698451200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008530","name":"Technology for Skillful Viniculture (SVtech)","doi-asserted-by":"publisher","award":["MIS 5046047"],"award-info":[{"award-number":["MIS 5046047"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"Technology for Skillful Viniculture (SVtech)","doi-asserted-by":"publisher","award":["NSRF 2014\u20132020"],"award-info":[{"award-number":["NSRF 2014\u20132020"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Competitiveness, Entrepreneurship and Innovation","award":["MIS 5046047"],"award-info":[{"award-number":["MIS 5046047"]}]},{"name":"Competitiveness, Entrepreneurship and Innovation","award":["NSRF 2014\u20132020"],"award-info":[{"award-number":["NSRF 2014\u20132020"]}]},{"name":"Greece and the European Union (European Regional Development Fund)","award":["MIS 5046047"],"award-info":[{"award-number":["MIS 5046047"]}]},{"name":"Greece and the European Union (European Regional Development Fund)","award":["NSRF 2014\u20132020"],"award-info":[{"award-number":["NSRF 2014\u20132020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>The development of agricultural robots is an increasingly popular research field aiming at addressing the widespread labor shortages in the farming industry and the ever-increasing food production demands. In many cases, multiple cooperating robots can be deployed in order to reduce task duration, perform an operation not possible with a single robot, or perform an operation more effectively. Building on previous results, this application paper deals with a cooperation strategy that allows two heterogeneous robots to cooperatively carry out grape harvesting, and its implementation is demonstrated. More specifically, the cooperative grape harvesting task involves two heterogeneous robots, where one robot (i.e., the expert) is assigned the grape harvesting task, whereas the second robot (i.e., the helper) is tasked with supporting the harvesting task by carrying the harvested grapes. The proposed cooperative harvesting methodology ensures safe and effective interactions between the robots. Field experiments have been conducted in order firstly to validate the effectiveness of the coordinated navigation algorithm and secondly to demonstrate the proposed cooperative harvesting method. The paper reports on the conclusions drawn from the field experiments, and recommendations for future enhancements are made. The potential of sophisticated as well as explainable decision-making based on logic for enhancing the cooperation of autonomous robots in agricultural applications is discussed in the context of mathematical lattice theory.<\/jats:p>","DOI":"10.3390\/robotics12060147","type":"journal-article","created":{"date-parts":[[2023,10,29]],"date-time":"2023-10-29T05:01:08Z","timestamp":1698555668000},"page":"147","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Cooperative Grape Harvesting Using Heterogeneous Autonomous Robots"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9045-3833","authenticated-orcid":false,"given":"Chris","family":"Lytridis","sequence":"first","affiliation":[{"name":"HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3780-5617","authenticated-orcid":false,"given":"Christos","family":"Bazinas","sequence":"additional","affiliation":[{"name":"HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7386-3788","authenticated-orcid":false,"given":"Ioannis","family":"Kalathas","sequence":"additional","affiliation":[{"name":"HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece"}]},{"given":"George","family":"Siavalas","sequence":"additional","affiliation":[{"name":"HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece"}]},{"given":"Christos","family":"Tsakmakis","sequence":"additional","affiliation":[{"name":"HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece"}]},{"given":"Theodoros","family":"Spirantis","sequence":"additional","affiliation":[{"name":"HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece"}]},{"given":"Eftichia","family":"Badeka","sequence":"additional","affiliation":[{"name":"HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6329-0533","authenticated-orcid":false,"given":"Theodore","family":"Pachidis","sequence":"additional","affiliation":[{"name":"HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1639-0627","authenticated-orcid":false,"given":"Vassilis G.","family":"Kaburlasos","sequence":"additional","affiliation":[{"name":"HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Fountas, S., Mylonas, N., Malounas, I., Rodias, E., Hellmann Santos, C., and Pekkeriet, E. (2020). Agricultural Robotics for Field Operations. Sensors, 20.","DOI":"10.3390\/s20092672"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"818","DOI":"10.1007\/s11119-020-09757-9","article-title":"Robots in Agriculture: Prospects, Impacts, Ethics, and Policy","volume":"22","author":"Sparrow","year":"2021","journal-title":"Precis. Agric."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/s43154-022-00077-6","article-title":"Robotics and Autonomous Systems for Net Zero Agriculture","volume":"3","author":"Pearson","year":"2022","journal-title":"Curr. Robot. Rep."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s10846-022-01793-z","article-title":"A Survey of Robotic Harvesting Systems and Enabling Technologies","volume":"107","author":"Droukas","year":"2023","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Bechar, A. (2021). Innovation in Agricultural Robotics for Precision Agriculture, Springer International Publishing. Progress in Precision Agriculture.","DOI":"10.1007\/978-3-030-77036-5"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"012042","DOI":"10.1088\/1755-1315\/1138\/1\/012042","article-title":"Global Trends in the Development of Agricultural Robotics","volume":"1138","author":"Starostin","year":"2023","journal-title":"IOP Conf. Ser. Earth Environ. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"107827","DOI":"10.1016\/j.compag.2023.107827","article-title":"Detection and Counting of Banana Bunches by Integrating Deep Learning and Classic Image-Processing Algorithms","volume":"209","author":"Wu","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Devanna, R.P., Milella, A., Marani, R., Garofalo, S.P., Vivaldi, G.A., Pascuzzi, S., Galati, R., and Reina, G. (2022). In-Field Automatic Identification of Pomegranates Using a Farmer Robot. Sensors, 22.","DOI":"10.3390\/s22155821"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Luo, L., Tang, Y., Zou, X., Wang, C., Zhang, P., and Feng, W. (2016). Robust Grape Cluster Detection in a Vineyard by Combining the AdaBoost Framework and Multiple Color Components. Sensors, 16.","DOI":"10.3390\/s16122098"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"108051","DOI":"10.1016\/j.compag.2023.108051","article-title":"Object Detection and Tracking on UAV RGB Videos for Early Extraction of Grape Phenotypic Traits","volume":"211","author":"Baja","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1002\/rob.21897","article-title":"Automated Crop Plant Detection Based on the Fusion of Color and Depth Images for Robotic Weed Control","volume":"37","author":"Gai","year":"2020","journal-title":"J. F. Robot."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Khan, N., Medlock, G., Graves, S., and Anwar, S. (2018, January 10\u201312). GPS Guided Autonomous Navigation of a Small Agricultural Robot with Automated Fertilizing System. Proceedings of the WCX World Congress Experience, Detroit, MI, USA. SAE Technical Papers.","DOI":"10.4271\/2018-01-0031"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1002\/rob.21889","article-title":"An Autonomous Strawberry-harvesting Robot: Design, Development, Integration, and Field Evaluation","volume":"37","author":"Xiong","year":"2020","journal-title":"J. F. Robot."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"100005","DOI":"10.1016\/j.atech.2021.100005","article-title":"Smart Applications and Digital Technologies in Viticulture: A Review","volume":"1","author":"Tardaguila","year":"2021","journal-title":"Smart Agric. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"107901","DOI":"10.1016\/j.compag.2023.107901","article-title":"Proximal Sensing for Geometric Characterization of Vines: A Review of the Latest Advances","volume":"210","author":"Moreno","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1100","DOI":"10.1002\/rob.21680","article-title":"A Robot System for Pruning Grape Vines","volume":"34","author":"Botterill","year":"2017","journal-title":"J. F. Robot."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"881904","DOI":"10.3389\/fpls.2022.881904","article-title":"Development of a Dual-Arm Rapid Grape-Harvesting Robot for Horizontal Trellis Cultivation","volume":"13","author":"Jiang","year":"2022","journal-title":"Front. Plant Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"149","DOI":"10.4081\/jae.2013.271","article-title":"Selective Spraying of Grapevine\u2019s Diseases by a Modular Agricultural Robot","volume":"44","author":"Oberti","year":"2013","journal-title":"J. Agric. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1007\/978-3-319-70833-1_21","article-title":"GRAPE: Ground Robot for VineyArd Monitoring and ProtEction","volume":"Volume 693","author":"Roure","year":"2018","journal-title":"Advances in Intelligent Systems and Computing"},{"key":"ref_20","unstructured":"Dos Santos, F.N., Sobreira, H., Campos, D., Morais, R., Moreira, A.P., and Contente, O. (2015, January 8\u201310). Towards a Reliable Monitoring Robot for Mountain Vineyards. Proceedings of the 2015 IEEE International Conference on Autonomous Robot Systems and Competitions ICARSC, Vila Real, Portugal."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Lytridis, C., Siavalas, G., Pachidis, T., Theocharis, S., Moschou, E., and Kaburlasos, V.G. (2023). Grape Maturity Estimation for Personalized Agrobot Harvest by Fuzzy Lattice Reasoning (FLR) on an Ontology of Constraints. Sustainability, 15.","DOI":"10.3390\/su15097331"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Reiser, D., Sehsah, E.-S., Bumann, O., Morhard, J., and Griepentrog, H. (2019). Development of an Autonomous Electric Robot Implement for Intra-Row Weeding in Vineyards. Agriculture, 9.","DOI":"10.3390\/agriculture9010018"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Bechar, A. (2021). Innovation in Agricultural Robotics for Precision Agriculture. Progress in Precision Agriculture, Springer.","DOI":"10.1007\/978-3-030-77036-5"},{"key":"ref_24","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_25","doi-asserted-by":"crossref","first-page":"107336","DOI":"10.1016\/j.compag.2022.107336","article-title":"Il A Review on Multirobot Systems in Agriculture","volume":"202","author":"Ju","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Mao, W., Liu, Z., Liu, H., Yang, F., and Wang, M. (2021). Research Progress on Synergistic Technologies of Agricultural Multi-Robots. Appl. Sci., 11.","DOI":"10.3390\/app11041448"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Tourrette, T., Deremetz, M., Naud, O., Lenain, R., Laneurit, J., and De Rudnicki, V. (2018, January 1\u20135). Close Coordination of Mobile Robots Using Radio Beacons: A New Concept Aimed at Smart Spraying in Agriculture. Proceedings of the 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain.","DOI":"10.1109\/IROS.2018.8593978"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/978-3-319-40379-3_17","article-title":"Multi Robot Cooperative Area Coverage, Case Study: Spraying","volume":"Volume 9716","author":"Janani","year":"2016","journal-title":"Lecture Notes in Computer Science"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Berger, G.S., Teixeira, M., Cantieri, A., Lima, J., Pereira, A.I., Valente, A., de Castro, G.G.R., 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"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Hameed, I.A. (2018, January 1\u20135). A Coverage Planner for Multi-Robot Systems in Agriculture. Proceedings of the 2018 IEEE International Conference on Real-time Computing and Robotics (RCAR), Kandima, Maldives.","DOI":"10.1109\/RCAR.2018.8621801"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Santos, L.C., Santos, F.N., Solteiro Pires, E.J., Valente, A., Costa, P., and Magalhaes, S. (2020, January 15\u201317). Path Planning for Ground Robots in Agriculture: A Short Review. Proceedings of the 2020 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Ponta Delgada, Portugal.","DOI":"10.1109\/ICARSC49921.2020.9096177"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"108089","DOI":"10.1016\/j.compeleceng.2022.108089","article-title":"A Deep Reinforcement Learning-Based Multi-Agent Area Coverage Control for Smart Agriculture","volume":"101","author":"Din","year":"2022","journal-title":"Comput. Electr. Eng."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2942","DOI":"10.1007\/978-981-16-9492-9_288","article-title":"Collaborative Path Planning for Agricultural Mobile Robots: A Review","volume":"Volume 861","author":"Wang","year":"2022","journal-title":"Lecture Notes in Electrical Engineering"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1007\/978-3-319-99582-3_22","article-title":"Trends in Development of UAV-UGV Cooperation Approaches in Precision Agriculture","volume":"Volume 11097 LNAI","author":"Vu","year":"2018","journal-title":"Lecture Notes in Computer Science"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.biosystemseng.2021.12.010","article-title":"Cooperation of Unmanned Systems for Agricultural Applications: A Case Study in a Vineyard","volume":"223","author":"Mammarella","year":"2022","journal-title":"Biosyst. Eng."},{"key":"ref_36","unstructured":"Iida, M., Harada, S., Sasaki, R., Zhang, Y., Asada, R., Suguri, M., and Masuda, R. (2017, January 16\u201319). Multi-Combine Robot System for Rice Harvesting Operation. Proceedings of the 2017 ASABE Annual International Meeting, Spokane, WA, USA."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Harik, E.H.C. (2023). Tractor-Robot Cooperation: A Heterogeneous Leader-Follower Approach. Robotics, 12.","DOI":"10.3390\/robotics12020057"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"121889","DOI":"10.1109\/ACCESS.2020.3006919","article-title":"Robotic Aubergine Harvesting Using Dual-Arm Manipulation","volume":"8","author":"Sepulveda","year":"2020","journal-title":"IEEE Access"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Davidson, J.R., Hohimer, C.J., Mo, C., and Karkee, M. (2017, January 16\u201319). Dual Robot Coordination for Apple Harvesting. Proceedings of the 2017 ASABE Annual International Meeting, Spokane, WA, USA.","DOI":"10.13031\/aim.201700567"},{"key":"ref_40","unstructured":"Conejero, M.N., Montes, H., Andujar, D., Bengochea-Guevara, J.M., Rodr\u00edguez, E., and Ribeiro, A. (2023). Precision Agriculture \u201923, Wageningen Academic Publishers."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Vrochidou, E., Tziridis, K., Nikolaou, A., Kalampokas, T., Papakostas, G.A., Pachidis, T.P., Mamalis, S., Koundouras, S., and Kaburlasos, V.G. (2021). An Autonomous Grape-Harvester Robot: Integrated System Architecture. Electronics, 10.","DOI":"10.3390\/electronics10091056"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Lytridis, C., Bazinas, C., Pachidis, T., Chatzis, V., and Kaburlasos, V.G. (2022). Coordinated Navigation of Two Agricultural Robots in a Vineyard: A Simulation Study. Sensors, 22.","DOI":"10.3390\/s22239095"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Kaburlasos, V.G. (2022). Lattice Computing: A Mathematical Modelling Paradigm for Cyber-Physical System Applications. Mathematics, 10.","DOI":"10.3390\/math10020271"},{"key":"ref_44","unstructured":"(2023, June 16). Robotnik Mobile Robots. Available online: https:\/\/robotnik.eu."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Badeka, E., Vrochidou, E., Tziridis, K., Nicolaou, A., Papakostas, G.A., Pachidis, T., and Kaburlasos, V.G. (2020, January 28\u201330). Navigation Route Mapping for Harvesting Robots in Vineyards Using UAV-Based Remote Sensing. Proceedings of the 2020 IEEE 10th International Conference on Intelligent Systems (IS), Varna, Bulgaria.","DOI":"10.1109\/IS48319.2020.9199958"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Xiaoyu, W., Caihong, L., Li, S., Ning, Z., and Hao, F. (2018, January 25\u201327). On Adaptive Monte Carlo Localization Algorithm for the Mobile Robot Based on ROS. Proceedings of the 2018 37th Chinese Control Conference (CCC), Wuhan, China.","DOI":"10.23919\/ChiCC.2018.8482698"},{"key":"ref_47","unstructured":"R\u00f6smann, C., Feiten, W., W\u00f6sch, T., Hoffmann, F., and Bertram, T. (2012, January 21\u201322). Trajectory Modification Considering Dynamic Constraints of Autonomous Robots. Proceedings of the 7th German Conference on Robotics, Munich, Germany."},{"key":"ref_48","first-page":"449","article-title":"Using ROS in Multi-Robot Systems: Experiences and Lessons Learned from Real-World Field Tests","volume":"Volume 707","author":"Valente","year":"2017","journal-title":"Studies in Computational Intelligence"},{"key":"ref_49","first-page":"3","article-title":"Reducing the Barrier to Entry of Complex Robotic Software: A MoveIt! Case Study","volume":"5","author":"Coleman","year":"2014","journal-title":"J. Softw. Eng. Robot."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Quaglia, G., Tagliavini, L., Colucci, G., Vorfi, A., Botta, A., and Baglieri, L. (2022). Design and Prototyping of an Interchangeable and Underactuated Tool for Automatic Harvesting. Robotics, 11.","DOI":"10.3390\/robotics11060145"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Bazinas, C., Vrochidou, E., Lytridis, C., and Kaburlasos, V.G. (2021). Time-Series of Distributions Forecasting in Agricultural Applications: An Intervals\u2019 Numbers Approach. Eng. Proc., 5.","DOI":"10.3390\/engproc20210050012"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Badeka, E., Karapatzak, E., Karampatea, A., Bouloumpasi, E., Kalathas, I., Lytridis, C., Tziolas, E., Tsakalidou, V.N., and Kaburlasos, V.G. (2023). A Deep Learning Approach for Precision Viticulture, Assessing Grape Maturity via YOLOv7. Sensors, 23.","DOI":"10.3390\/s23198126"}],"container-title":["Robotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-6581\/12\/6\/147\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:13:33Z","timestamp":1760130813000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-6581\/12\/6\/147"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,28]]},"references-count":52,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["robotics12060147"],"URL":"https:\/\/doi.org\/10.3390\/robotics12060147","relation":{},"ISSN":["2218-6581"],"issn-type":[{"value":"2218-6581","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,28]]}}}