A technical review on navigation systems of agricultural autonomous off-road vehicles

被引:156
|
作者
Mousazadeh, Hossein [1 ]
机构
[1] Univ Tehran, Dept Agr Machinery Engn, Fac Agr Engn & Technol, Univ Coll Agr & Nat Resources, Karaj, Iran
关键词
Autonomous; Navigation; Machine vision; Robot; Kalman filter; MACHINE VISION; ROW GUIDANCE; ROBOT; PLATFORM; CONTROLLER; ALGORITHM; BEHAVIOR; NETWORK; MODEL;
D O I
10.1016/j.jterra.2013.03.004
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With the predicted increase in world population to over 10 billion, by the year 2050, growth in agricultural output needs to be continued. Considering this, autonomous vehicles application in precision agriculture is one of the main issues to be regarded noteworthy to improve the efficiency. In this research many papers on autonomous farm vehicles are reviewed from navigation systems viewpoint. All navigation systems are categorized in six classes: dead reckoning, image processing, statistical based developed algorithms, fuzzy logic control, neural network and genetic algorithm, and Kalman filter based. Researches in many agricultural operations from water monitoring to aerial crop scouting revealed that the centimeter level accuracy in all techniques is available and the velocity range for evaluated autonomous vehicles almost is smaller than 1 m/s. Finally it would be concluded although many developments in agricultural automation using different techniques and algorithms are obtained especially in recent years, more works are required to acquire farmer's consensus about autonomous vehicles. Additionally some issues such as safety, economy, implement standardization and technical service support in the entire world are merit to consideration. (C) 2013 ISTVS. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:211 / 232
页数:22
相关论文
共 50 条
  • [21] Obstacle Detection and Terrain Classification for Autonomous Off-Road Navigation
    R. Manduchi
    A. Castano
    A. Talukder
    L. Matthies
    Autonomous Robots, 2005, 18 : 81 - 102
  • [22] Path Planning and Tracking Algorithms for Autonomous Off-Road Vehicles
    Frison, Gianluca
    Tota, Antonio
    Dimauro, Luca
    Velardocchia, Mauro
    ADVANCES IN ITALIAN MECHANISM SCIENCE, IFTOMM ITALY, VOL 2, 2024, 164 : 281 - 289
  • [23] Quantitative assessment of modelling and simulation tools for autonomous navigation of military vehicles over off-road terrains
    Cole M.
    Lucas C.
    Kulkarni K.
    Carruth D.
    Hudson C.
    Jayakumar P.
    Gorsich D.
    International Journal of Vehicle Performance, 2020, 6 (03) : 327 - 355
  • [24] Improving Trajectory Tracking Accuracy for Faster and Safer Autonomous Navigation of Ground Vehicles in Off-Road Settings
    Gregory, Jason M.
    Warnell, Garrett
    Fink, Jonathan
    Gupta, Satyandra K.
    2021 IEEE INTERNATIONAL SYMPOSIUM ON SAFETY, SECURITY, AND RESCUE ROBOTICS (SSRR), 2021, : 204 - 209
  • [25] FOOTWEAR FOR OFF-ROAD VEHICLES
    THOMAS, A
    ENGINEERING, 1974, 214 (05): : 388 - 391
  • [26] Passive perception system for day/night autonomous off-road navigation
    Rankin, AL
    Bergh, CF
    Goldberg, SB
    Bellutta, P
    Huertas, A
    Matthies, LH
    UNMANNED GROUND VEHICLE TECHNOLOGY VII, 2005, 5804 : 343 - 358
  • [27] Global-referenced navigation grids for off-road vehicles and environments
    Rovira-Mas, Francisco
    ROBOTICS AND AUTONOMOUS SYSTEMS, 2012, 60 (02) : 278 - 287
  • [28] Stereo vision based terrain mapping for off-road autonomous navigation
    Rankin, Arturo L.
    Huertas, Andres
    Matthies, Larry H.
    UNMANNED SYSTEMS TECHNOLOGY XI, 2009, 7332
  • [29] Algorithmic solution for autonomous vision-based off-road navigation
    Kolesnik, M
    Paar, G
    Bauer, A
    Ulm, M
    ENHANCED AND SYNTHETIC VISION 1998, 1998, 3364 : 230 - 247
  • [30] The Impact of the Accuracy of Terrain Surface Data on the Navigation of Off-Road Vehicles
    Rada, Josef
    Rybansky, Marian
    Dohnal, Filip
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2021, 10 (03)