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Autonomous pollination of individual kiwifruit flowers: Toward a robotic kiwifruit pollinator
Authors:Henry Williams  Mahla Nejati  Salome Hussein  Nicky Penhall  Jong Yoon Lim  Mark Hedley Jones  Jamie Bell  Ho Seok Ahn  Stuart Bradley  Peter Schaare  Paul Martinsen  Mohammad Alomar  Purak Patel  Matthew Seabright  Mike Duke  Alistair Scarfe  Bruce MacDonald
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.
Keywords:convolution neural networks  horticulture  kiwifruit  machine vision  neural networking  orchards  pollination  robotics
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