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Autonomous Robots

, Volume 13, Issue 3, pp 241–258 | Cite as

An Autonomous Robot for Harvesting Cucumbers in Greenhouses

  • E.J. van Henten
  • J. Hemming
  • B.A.J. van Tuijl
  • J.G. Kornet
  • J. Meuleman
  • J. Bontsema
  • E.A. van Os
Article

Abstract

This paper describes the concept of an autonomous robot for harvesting cucumbers in greenhouses. A description is given of the working environment of the robot and the logistics of harvesting. It is stated that for a 2 ha Dutch nursery, 4 harvesting robots and one docking station are needed during the peak season. Based on these preliminaries, the design specifications of the harvest robot are defined. The main requirement is that a single harvest operation may take at most 10 s. Then, the paper focuses on the individual hardware and software components of the robot. These include, the autonomous vehicle, the manipulator, the end-effector, the two computer vision systems for detection and 3D imaging of the fruit and the environment and, finally, a control scheme that generates collision-free motions for the manipulator during harvesting. The manipulator has seven degrees-of-freedom (DOF). This is sufficient for the harvesting task. The end-effector is designed such that it handles the soft fruit without loss of quality. The thermal cutting device included in the end-effector prevents the spreading of viruses through the greenhouse. The computer vision system is able to detect more than 95% of the cucumbers in a greenhouse. Using geometric models the ripeness of the cucumbers is determined. A motion planner based on the A*-search algorithm assures collision-free eye-hand co-ordination. In autumn 2001 system integration took place and the harvesting robot was tested in a greenhouse. With a success rate of 80%, field tests confirmed the ability of the robot to pick cucumbers without human interference. On average the robot needed 45 s to pick one cucumber. Future research focuses on hardware and software solutions to improve the picking speed and accuracy of the eye-hand co-ordination of the robot.

autonomous robot robotics manipulator end-effector computer vision stereo-vision collision avoidance motion planning greenhouse cucumber harvesting 

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References

  1. Anonymous, 2000. Land en tuinbouwcijfers 2000 [in Dutch]. LEI/CBS, 's Gravenhage, The Netherlands.Google Scholar
  2. Arima, S. and Kondo, N. 1999. Cucumber harvesting robot and plant training system. Journal of Robotics and Mechatronics, 11(3):208-212.Google Scholar
  3. Boyse, J.W. 1979. Interference detection among solids and surfaces. Communications of the ACM, 22(1):3-9.Google Scholar
  4. Craig, J.J. 1989. Introduction to Robotics, Addison-Wesley, Reading: Mass., USA.Google Scholar
  5. Edan, Y. 1995. Design of an autonomous agricultural robot. Applied Intelligence, 5:41-50.Google Scholar
  6. Gieling, Th.H., Van Henten, E.J., Van Os, E.A., Sakaue, O., and Hendrix, A.T.M. 1996. Conditions, demands and technology for automatic harvesting of fruit vegetables. Acta Horticulturae, 440: 360-365.Google Scholar
  7. Hayashi, S. and Sakaue, O. 1996. Tomato harvesting by robotic system. ASAE Annual International Meeting, Phoenix, Arizona, USA, Paper 963067.Google Scholar
  8. Heikkilä, J. and Silvén, O. 1997. A four-step camera calibration procedure with implicit image correction. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), San Juan, Puerto Rico, pp. 1106-1112.Google Scholar
  9. Hemming, J. and Van Der Meij, M.J. 2000. Het visionsysteem van een oogstrobot. IMAG,Wageningen, The Netherlands, IMAG Report V 2001-12.Google Scholar
  10. Hendrix, A.T.M. 1993. Taaktijden voor de groenteteelt onder glas [in Dutch]. IMAG, Wageningen, The Netherlands, IMAG Report 93-14.Google Scholar
  11. Herman, M. 1986. Fast, three-dimensional, collision-free motion planning. In Proceedings of the IEEE International Conference on Robotics and Automation, San Fransisco, California, USA, pp. 1056-1063.Google Scholar
  12. Hwang, Y.K. and Ahuja, N. 1992. Gross motion planning—a survey. ACM Computing Surveys, 24(3):219-291.Google Scholar
  13. Kondo, K. 1991. Motion planning with six degrees of freedom by multistrategic bidirectional heuristic free-space enumeration. IEEE Transactions on Robotics and Automation, 7(3):267-277.Google Scholar
  14. Kondo, N., Monta, M., and Fujiura, T. 1996. Fruit harvesting robots in Japan. Advances in Space Research, 18(1/2):181-184.Google Scholar
  15. Kornet, J.G. and Meuleman, J. 1999. Werkwijze en inrichting voor het detecteren van waterrijke objecten [in Dutch]. Patent number 1013780.Google Scholar
  16. Langers, R.A. 1998a. Modelstructuren voor het schatten van het volume c.q. gewicht van komkommers met computer vision [in Dutch]. IMAG,Wageningen, The Netherlands, IMAGReport P98-25.Google Scholar
  17. Langers, R.A. 1998b. Reconstructie van volume en gewicht van komkommers met behulp van de distance transform [in Dutch]. IMAG, Wageningen, The Netherlands, IMAG Report P98-38.Google Scholar
  18. Latombe, J.C. 1991. Robot Motion Planning, Kluwer Academic Publishers: Boston, USA.Google Scholar
  19. Lin, M.C. and Gottschalk, S. 1998. Collision detection between geometric models: A survey. In Proceedings 8th IMA Conference on the Mathematics of Surfaces, Winchester, UK, pp. 1-20.Google Scholar
  20. Meuleman, J., Van Heulen, S.F., Kornet, J.G., and Peters, D.G. 2000. Image analysis for robot harvesting of cucumbers. EurAgEng 2000, The European Conference of Agricultural Engineers, Warwick, UK, Paper No. 00-AE-003.Google Scholar
  21. Pearl, J. 1984. Heuristics: Intelligent Search Strategies for Computer Problem Solving, Addision-Wesley: Reading, Mass., USA.Google Scholar
  22. Russell, S. and Norvig, P. 1995. Artificial Intelligence: A Modern Approach, Prentice Hall: Englewood Cliffs, New Jersey, USA.Google Scholar
  23. Schenk, E.J. 2000. Modelvorming, voorwaartse kinematica, inverse kinematica met botsingsdetectie en padplanning van een 7 DOF manipulator systeem voor het automatisch oogsten van komkommers [in Dutch]. IMAG, Wageningen, The Netherlands, IMAG Report V 2000-77.Google Scholar
  24. Sévilla, F., Balerin, S., and Thompson, P. 1992. Control of an agricultural robotic arm based on a mobile platform. AG Eng 92, Agricultural Engineering International Conference, Uppsala, Sweden.Google Scholar
  25. Tillet, N.D. 1993. Robotic manipulators in horticulture: A review. Journal of Agricultural Engineering Research, 55:89-105.Google Scholar
  26. Van Dijk, G. 1999. Modelvorming en padplanning van een 6 DOF manipulator voor het oogsten van komkommers [in Dutch]. IMAG, Wageningen, The Netherlands, IMAG Report V99-04.Google Scholar
  27. Van Kollenburg-Crisan, L.M., Sjwed, D.A., Wennekes, P.C., and Kornet, J.G. 1999. Method and Device for Cutting the Stalks of Fruits. Patent number 1008161.Google Scholar
  28. Van Kollenburg-Crisan, L.M., Wennekes, P., and Werkhoven, C. 1997. Development of a mechatronic system for automatic harvesting of cucumbers. In Proceedings of BIO-ROBOTICS 97, The International Workshop on Robotics and Automated Machinery for Bio-Productions, Valencia, Spain, pp. 143-148.Google Scholar
  29. Zhang, Z.Y. 1999. Flexible camera calibration by viewing a plane from unknown orientations. In Proceedings of the 7th IEEE Conference on Computer Vision, ICCV99, Kerkyra, Greece, pp. 666-673.Google Scholar

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • E.J. van Henten
    • 1
  • J. Hemming
    • 1
  • B.A.J. van Tuijl
    • 1
  • J.G. Kornet
    • 1
  • J. Meuleman
    • 1
  • J. Bontsema
    • 1
  • E.A. van Os
    • 1
  1. 1.Institute of Agricultural and Environmental Engineering (IMAG B.V.)WageningenThe Netherlands

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