Stereo Vision-Based Path Planning System for an Autonomous Harvester

  • Saurabh Sinalkar
  • Binoy B. Nair
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1118)


Autonomy in agricultural machinery is an important need for smart and precision farming. The productivity and accuracy of farm machinery can be drastically increased by employing autonomous path planning systems for the tedious task of manually steering vehicles which would thereby save the time of producers and reduce driver fatigue. The goal of this paper is to develop a stereo vision-based path planning system for an autonomous onion harvester. The proposed solution consists of identifying the crop rows through deep learning-based semantic segmentation of images streamed through a stereo vision camera. Segmentation information is used along with image depth map data to determine navigation waypoints for the harvester to traverse. The developed system was designed and tested on an Indian onion field dataset which gives considerably good results.


Stereo vision Path planning Semantic segmentation Deep learning 


  1. 1.
    Badrinarayanan, V., Kendall, A., Cipolla, R.: SegNet: a deep convolutional encoder-decoder architecture for image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39, 2481–2495 (2017)CrossRefGoogle Scholar
  2. 2.
    Kise, M., Zhang, Q., Rovira Más, F.: A stereovision-based crop row detection method for tractor-automated guidance. Biosyst. Eng. 90, 357–367 (2005)CrossRefGoogle Scholar
  3. 3.
    Ball, D., Upcroft, B., Wyeth, G., Corke, P., English, A., Ross, P., Patten, T., Fitch, R., Sukkarieh, S., Bate, A.: Vision-based obstacle detection and navigation for an agricultural robot. J. Field Rob. 33, 1107–1130 (2016)CrossRefGoogle Scholar
  4. 4.
    RoviraMás, F., Zhang, Q., Reid, J.F.: Automated agricultural equipment navigation using stereo disparity images. Trans. ASAE. 47, 1289–1300 (2013)CrossRefGoogle Scholar
  5. 5.
    English, A., Ross, P., Ball, D., Upcroft, B., Corke, P.: Learning crop models for vision-based guidance of agricultural robots. In: IEEE International Conference on Intelligent Robot and Systems, pp. 1158–1163 (2015)Google Scholar
  6. 6.
    Zhang, S., Wang, Y., Zhu, Z., Li, Z., Du, Y., Mao, E.: Tractor path tracking control based on binocular vision. Inf. Process. Agric. 5, 422–432 (2018)Google Scholar
  7. 7.
    García-Santillán, I.D., Montalvo, M., Guerrero, J.M., Pajares, G.: Automatic detection of curved and straight crop rows from images in maize fields. Biosyst. Eng. 156, 61–79 (2017)CrossRefGoogle Scholar
  8. 8.
    Christiansen, P., Rückert, U., Jørgensen, R.N., Karstoft, H., Kragh, M., Korthals, T.: Multi-modal detection and mapping of static and dynamic obstacles in agriculture for process evaluation. Front. Robot AI, vol. 5 (2018)Google Scholar
  9. 9.
    Adhvaryu, A.D., Adarsh, S., Ramchandran, K.I.: Design of fuzzy based intelligent controller for autonomous mobile robot navigation. In: 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 841–846 (2017)Google Scholar
  10. 10.
    Varma, V.S.K.P., Adarsh, S., Ramachandran, K.I., Nair, B.B.: Real time detection of speed hump/bump and distance estimation with deep learning using GPU and ZED stereo camera. Procedia Comput. Sci. 143, 988–997 (2018)CrossRefGoogle Scholar
  11. 11.
    Gonzalez-de-Santos, P., Romeo, J., Emmi, L., Guerrero, J., García-Santillán, I., Guijarro, M., Pajares, G., Montalvo, M., Campos, Y.: Machine-vision systems selection for agricultural vehicles: a guide. J. Imaging 2, 34 (2016)CrossRefGoogle Scholar
  12. 12.
    Kamilaris, A., Prenafeta-Boldú, F.X.: A review of the use of convolutional neural networks in agriculture. J. Agric. Sci. 1–11 (2018)Google Scholar
  13. 13.
    Dhingra, M.: FISITA 2018. In: Autocar Professional. p. 37 (2018)Google Scholar
  14. 14.
    ZED Stereo Camera – Stereolabs.

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Saurabh Sinalkar
    • 1
  • Binoy B. Nair
    • 1
    • 2
  1. 1.Department of Electronics and Communication EngineeringAmrita School of Engineering, Amrita Vishwa VidyapeethamCoimbatoreIndia
  2. 2.SIERS Research LaboratoryAmrita School of Engineering, Amrita Vishwa VidyapeethamCoimbatoreIndia

Personalised recommendations