Research on Machine Vision Based Agricultural Automatic Guidance Systems

  • Bin Liu
  • Gang Liu
  • Xue Wu
Part of the The International Federation for Information Processing book series (IFIPAICT, volume 258)

With the concept of precision agricultural was proposed, the research of agricultural automatic vehicle was paid more attention to in the world. The fundamental element of machine vision based agricultural automatic navigation system was presented in this paper. It includes path finding, location &path tracing and motion controlling. The image processing, automatic control and sensor fusion techniques are the key for autonomous vehicle systems.


Agricultural vehicle Machine vision Guidance Automatic control 


  1. Benson, E. R., Reid, J. F., Zhang, Q., Machine-vision based guidance system for agricultural grain harvester using cutedge detection [J]. Biosystem Engineering, 2003, 86(4): 389-398.CrossRefGoogle Scholar
  2. Benson, E., Stombaugh, T., Noguchi, N., Will, J., Reid, J.F., 1998. An evaluation of a geomagnetic direction sensor for vehicle guidance in precision agriculture applications. ASAE Paper 983203. ASAE. St. Joseph, MI.Google Scholar
  3. Han, S., Zhang, Q., Reid, J.F., A guidance directrix approach to vision-based vehicle guidance systems [J]. Computers and Electronics in Agriculture, 2004, 43: 179-195.CrossRefGoogle Scholar
  4. Jiang Zhengrong, Implementation and Application of Computer Technique for Identification of Weed [J]. Weed science, 1999, 4: 2-5. (in Chinese)Google Scholar
  5. Reid, J.F., Zhang, Q., Noguchi, N., Agricultural automatic guidance research in North America [J]. Computers and Electronics in Agriculture, 2000, 25: 155-167.CrossRefGoogle Scholar
  6. Søgaard, H.T., Olsen, H.J., Determination of crop rows by image analysis without segmentation [J]. Computers and Electronics in Agriculture, 2003, 38: 141-158.CrossRefGoogle Scholar
  7. Stombaugh, T., Benson, E., Hummel, J.W., 1998. Automatic guidance of agricultural vehicles at high field speeds. ASAE Paper 983110. St. Joseph, MI.Google Scholar
  8. Sun Yuanyi, Zhang Shaolei, Li Wei, Guidance lane detection for pesticide spraying robot in cotton fields [J]. Journal of Tsinghua University (Science & Technology), 2007, 47(2): 206-209. (in Chinese)Google Scholar
  9. Tian Haiqing, Ying Yibin, Zhang Fangming, Development of Automatic Control Technique for Agricultural Vehicle Guidance [J]. Transactions of The Chinese Society of Agricultural Machinery, 2005, 36(7): 148-152. (in Chinese)Google Scholar
  10. Leemans, V., Destain, M.-F., Application of the Hough Transform for Seed Row Localisation using Machine Vision [J]. Biosystems Engineering, 2006, 94(3): 325-336.CrossRefGoogle Scholar
  11. Woebbecke, D.M., Meyer, G.E., Von Bargen, K. et al. Color indices for weed identification under various soil, residue, and lighting conditions [J]. Trans of the ASAE, 1995, 38(1): 259-269.CrossRefGoogle Scholar
  12. Wu, D., Zhang, Q., Reid. J.F., Qiu, H., Benson, E.R., 1998. Model Recognition and Simulation of an E/H Steering Controller on Off-Road Equipment. In: Nair, S.S., Mistry, S.I. (Eds). Fluid Power Systems and Technology 1998, ASME, New York, pp. 55-60.Google Scholar
  13. Zhang Fangming, Ying Yibin, Review of Machine Vision Research in Agricultural Vehicle Guidance [J]. Transactions of The Chinese Society of Agricultural Machinery, 2005, 36 (5): 133-136. (in Chinese)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2008

Authors and Affiliations

  • Bin Liu
    • 1
  • Gang Liu
    • 1
  • Xue Wu
    • 2
  1. 1.Key Laboratory of Modern Precision Agriculture System Integration ResearchChina Agricultural UniversityChina
  2. 2.College of Mechanical Engineering and AutomationBeijing Technology and Business UniversityChina

Personalised recommendations