A Review of Robots, Perception, and Tasks in Precision Agriculture

被引:60
作者
Botta, Andrea [1 ]
Cavallone, Paride [1 ]
Baglieri, Lorenzo [1 ]
Colucci, Giovanni [1 ]
Tagliavini, Luigi [1 ]
Quaglia, Giuseppe [1 ]
机构
[1] Politecn Torino, DIMEAS Dept Mech & Aerosp Engn, I-10129 Turin, Italy
来源
APPLIED MECHANICS | 2022年 / 3卷 / 03期
关键词
precision agriculture; mobile robotics; smart farming; agricultural sensors; ABOVEGROUND BIOMASS; AUTOMATIC GUIDANCE; HARVESTING ROBOT; MOBILE ROBOT; WATER-STRESS; PEST-CONTROL; AREA INDEX; LIDAR DATA; SOIL; FRUIT;
D O I
10.3390/applmech3030049
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This review reports the recent state of the art in the field of mobile robots applied to precision agriculture. After a brief introduction to precision agriculture, the review focuses on two main topics. First, it provides a broad overview of the most widely used technologies in agriculture related to crop, field, and soil monitoring. Second, the main robotic solutions, with a focus on land-based robots, and their salient features are described. Finally, a short case study about a robot developed by the authors is introduced. This work aims to collect and highlight the most significant trends in research on robotics applied to agriculture. This review shows that the most studied perception solutions are those based on vision and cloud point detection and, following the same trend, most robotic solutions are small robots dedicated exclusively to monitoring tasks. However, the robotisation of other agricultural tasks is growing.
引用
收藏
页码:830 / 854
页数:25
相关论文
共 219 条
  • [1] Adamchuk V., 2015, Soil Survey Manual. Natural Resources Conservation Service. US Department of Agriculture Handbook
  • [2] Design and development of a semi-autonomous agricultural vineyard sprayer: Human-robot interaction aspects
    Adamides, George
    Katsanos, Christos
    Constantinou, Ioannis
    Christou, Georgios
    Xenos, Michalis
    Hadzilacos, Thanasis
    Edan, Yael
    [J]. JOURNAL OF FIELD ROBOTICS, 2017, 34 (08) : 1407 - 1426
  • [3] Remote sensing of drought: Progress, challenges and opportunities
    AghaKouchak, A.
    Farahmand, A.
    Melton, F. S.
    Teixeira, J.
    Anderson, M. C.
    Wardlow, B. D.
    Hain, C. R.
    [J]. REVIEWS OF GEOPHYSICS, 2015, 53 (02) : 452 - 480
  • [4] Alenya G., 2011, 2011 IEEE International Conference on Robotics and Automation (ICRA 2011), P3408, DOI 10.1109/ICRA.2011.5980092
  • [5] An Autonomous Seeder for Maize Crop
    Ali, Amir Asghar
    Zohaib, Muhammad
    Mehdi, Syed Atif
    [J]. PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON ROBOTICS AND ARTIFICIAL INTELLIGENCE, ICRAI 2019, 2019, : 42 - 47
  • [6] Stem Volume and Above-Ground Biomass Estimation of Individual Pine Trees From LiDAR Data: Contribution of Full-Waveform Signals
    Allouis, Tristan
    Durrieu, Sylvie
    Vega, Cedric
    Couteron, Pierre
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2013, 6 (02) : 924 - 934
  • [7] Allred BJ, 2008, BOOKS SOIL PLANT ENV, P1
  • [8] Using depth cameras to extract structural parameters to assess the growth state and yield of cauliflower crops
    Andujar, Dionisio
    Ribeiro, Angela
    Fernandez-Quintanilla, Cesar
    Dorado, Jose
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2016, 122 : 67 - 73
  • [9] [Anonymous], 2020, Agrobot Bug Vacuum
  • [10] [Anonymous], 2019, CARRE ANATIS by CARRE