Lavender Autonomous Navigation with Semantic Segmentation at the Edge

被引:0
作者
Navone, Alessandro [1 ]
Romanelli, Fabrizio [2 ]
Ambrosio, Marco [1 ]
Martini, Mauro [1 ]
Angarano, Simone [1 ]
Chiaberge, Marcello [1 ]
机构
[1] Politecn Torino, Dept Elect & Telecommun, I-10129 Turin, Italy
[2] Univ Roma Tor Vergata, Dept Civil Engn & Comp Engn, I-00133 Rome, Italy
来源
MACHINE LEARNING AND PRINCIPLES AND PRACTICE OF KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2023, PT III | 2025年 / 2135卷
关键词
Autonomous Navigation; Semantic Segmentation; Precision Agriculture; VINEYARD;
D O I
10.1007/978-3-031-74633-8_18
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Achieving success in agricultural activities heavily relies on precise navigation in row crop fields. Recently, segmentation-based navigation has emerged as a reliable technique when GPS-based localization is unavailable or higher accuracy is needed due to vegetation or unfavorable weather conditions. It also comes in handy when plants are growing rapidly and require an online adaptation of the navigation algorithm. This work applies a segmentation-based visual agnostic navigation algorithm to lavender fields, considering both simulation and real-world scenarios. The effectiveness of this approach is validated through a wide set of experimental tests, which show the capability of the proposed solution to generalize over different scenarios and provide highly-reliable results.
引用
收藏
页码:280 / 291
页数:12
相关论文
共 23 条
[1]   Deep Semantic Segmentation at the Edge for Autonomous Navigation in Vineyard Rows [J].
Aghi, Diego ;
Cerrato, Simone ;
Mazzia, Vittorio ;
Chiaberge, Marcello .
2021 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2021, :3421-3428
[2]   Vineyard Autonomous Navigation in the Echord plus plus GRAPE Experiment [J].
Astolfi, Pietro ;
Gabrielli, Alessandro ;
Bascetta, Luca ;
Matteucci, Matteo .
IFAC PAPERSONLINE, 2018, 51 (11) :704-709
[3]  
Bianchi L., 2023, 2023 INT C CONTR AUT, P01, DOI [10.1109/ICCAD57653.2023.10152399, DOI 10.1109/ICCAD57653.2023.10152399]
[4]  
Bigelow D. P., 2017, Economic Information Bulletin - USDA Economic Research Service
[5]   The Future Challenges of Food and Agriculture: An Integrated Analysis of Trends and Solutions [J].
Calicioglu, Ozgul ;
Flammini, Alessandro ;
Bracco, Stefania ;
Bellu, Lorenzo ;
Sims, Ralph .
SUSTAINABILITY, 2019, 11 (01)
[6]  
Cerrato S., 2021, A deep learning driven algorithmic pipeline for autonomous navigation in row-based crops
[7]   2D and 3D data fusion for crop monitoring in precision agriculture [J].
Comba, Lorenzo ;
Biglia, Alessandro ;
Aimonino, Davide Ricauda ;
Barge, Paolo ;
Tortia, Cristina ;
Gay, Paolo .
2019 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR AGRICULTURE AND FORESTRY (METROAGRIFOR), 2019, :62-67
[8]  
Deshmukh Deepak, 2021, Hybrid Intelligent Systems. 20th International Conference on Hybrid Intelligent Systems (HIS 2020). Advances in Intelligent Systems and Computing (AISC 1375), P157, DOI 10.1007/978-3-030-73050-5_16
[9]   A Survey of Robotic Harvesting Systems and Enabling Technologies [J].
Droukas, Leonidas ;
Doulgeri, Zoe ;
Tsakiridis, Nikolaos L. L. ;
Triantafyllou, Dimitra ;
Kleitsiotis, Ioannis ;
Mariolis, Ioannis ;
Giakoumis, Dimitrios ;
Tzovaras, Dimitrios ;
Kateris, Dimitrios ;
Bochtis, Dionysis .
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2023, 107 (02)
[10]   Deep learning models for plant disease detection and diagnosis [J].
Ferentinos, Konstantinos P. .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2018, 145 :311-318