Investigation of Depth Camera Potentials for Variable-Rate Sprayers

Highlights A commercial depth camera with a custom-designed graphical user interface was evaluated to detect tree canopy. Measurement variations under different indoor conditions were negligible for practical applications. Measurement errors ranged from 2.8% to 15.8%, which were acceptable for outdoor applications. Variation of crabapple canopy detection rate was less than 6% from sunrise to sunset. Abstract. To reduce crop protection product use and environmental impacts while maintaining application efficacy and convenience for applicators, an automatic variable rate sprayer coupled with a canopy detection sensor is required. A commercial depth camera was tested as a means of detecting the canopy of ornamental and tree crops for the sprayer. A custom-designed graphical user interface was developed to control the depth camera and save RGB and IR images and depth data to a local computer. Indoor evaluations showed that measurements could be influenced by the temperature and illumination; however, the influence was minimal, with a relative error of less than 1% and a maximum difference of 14 mm between the average measurements. The depth camera was able to detect a 31% to 72% area of a 20-mm wide target, and the rates went up 72% to 89% when the target width increased to 40 mm. The depth camera showed acceptable performance in detecting canopy contour changes and had measurement errors of 2.8% to 15.3% while detecting the distances to outdoor crabapple and oak trees. In addition, the depth camera detected tree canopy in various outdoor conditions from sunrise to sunset with reasonable accuracy (less than 10% of relative errors). In terms of measurement stability, the depth camera detected crabapple canopy with less than 6% variations under various illuminations between sunrise and sunset. The results suggested that the performance of the depth camera was adequate for detecting canopy under outdoor conditions for future variable-rate spray applications in ornamental and tree crop production. In addition, the study outlined the performance of the depth camera, which provided a guideline for future applications. Keywords: Machine Vision, Precision Agriculture, Specialty Crop, Stereo Vision, Variable Rate Application.