Journal of Field Robotics · 2019 · 96 citations · 35 references
AgricultureAutonomous SystemsPlant SciencesAgricultural RoboticsMachine VisionRoboticsPollination BiologyPollination ControlPollination In Agricultural SystemsPollination ManagementArtificial PollinationAutomated PollinationConvolutionMachine Vision SensingMachine Vision SensorsMachine Vision SystemsPollination Control SystemsRobotic Pollination
Abstract There is an increasing concern that the traditional approach of natural kiwifruit pollination by bees may not be sustainable. The alternatives are currently too costly for most growers due to high labor requirements or inefficient usage of expensive pollen. This paper presents a performance evaluation of a novel kiwifruit pollinating robot designed to provide a more efficient, reliable, and cost‐effective means of producing kiwifruit. The robot comprises a novel air‐assisted sprayer, a machine vision system employing convolution neural networks, and a flower targeting system for efficient and effective application of pollen to individual flowers. We show that this pollination system is capable of individually targeting and pollinating 79.5% of flowers at 3.5 km/hr while using comparable amounts of pollen to commercial Cambrian operators. Furthermore, flowers that were successfully pollinated at 1 km/hr grew into the first robotically pollinated kiwifruit which were comparable in quality to commercially grown kiwifruit. However, the overall fruit set was found to be well below commercial requirements and further work on increasing the overall yield is required.
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