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Distance-based control system for machine vision-based selective spraying
Transactions of the ASAE
  • Brian L. Steward, Iowa State University
  • Lei F. Tian, University of Illinois at Urbana-Champaign
  • Lie Tang, The Royal Veterinary and Agricultural University
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Publication Version
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For effective operation of a selective sprayer with real–time local weed sensing, herbicides must be delivered accurately to weed targets in the field. With a machine vision–based selective spraying system, acquiring sequential images and switching nozzles on and off at the correct locations are critical. An MS Windows–based imaging system was interfaced with a real–time embedded selective spray controller system to accomplish control tasks based on distance traveled. A machine vision–based sensing system and selective herbicide control system was developed and installed on a sprayer. A finite state machine (FSM) model was employed for controller design, and general design specifications were developed for determining the travel distance between states. The spatial application accuracy of the system was measured in the field using artificial targets. The system operated with an overall hit accuracy of 91% with no statistical evidence of hit accuracy or mean pattern length being dependent on vehicle speed. Significant differences in pattern length variance and mean pattern width were detected across speed levels ranging from 3.2 to 14 km/h. Spray patterns tended to shift relative to the target at higher travel speeds.

This article is from Transactions of the ASAE, 45, no. 5 (2002): 1255–1262.

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American Society of Agricultural Engineers
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Citation Information
Brian L. Steward, Lei F. Tian and Lie Tang. "Distance-based control system for machine vision-based selective spraying" Transactions of the ASAE Vol. 45 Iss. 5 (2002) p. 1255 - 1262
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