Towards Closing the Loop in Robotic Pollination for Indoor Farming via Autonomous Microscopic Inspection

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Overview Video

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Spotlights

Closed-loop navigation to the flower

We utilize deep learning based flower detection and pose estimation method to facilitate the visual servoing algorithm.

Autofocusing Microscopic Subsystem to check for pollen quantity

The autofocusing algorithm, working with our mechatronics subsystem, enables us to bring a cheap handheld microscope (~$40) onto any strawberry flower to inspect its pollen deposition.

Vibratory Pollination with Independent Experiment Results

We experimentally validated our novel pollination tool on 64 strawberry plants. The flowers pollinated through our tool exhibited 30% increase in total fruit mass and overall improvement in fruit quality.

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Abstract

Effective pollination is a key challenge for indoor farming, since bees struggle to navigate without the sun. While a variety of robotic system solutions have been proposed, it remains difficult to autonomously check that a flower has been sufficiently pollinated to produce high-quality fruit, which is especially critical for self-pollinating crops such as strawberries. To this end, this work proposes a novel robotic system for indoor farming. The proposed hardware combines a 7-degree-of-freedom (DOF) manipulator arm with a custom end-effector, comprised of an endoscope camera, a 2-DOF microscope subsystem, and a custom vibrating pollination tool; this is paired with algorithms to detect and estimate the pose of strawberry flowers, navigate to each flower, pollinate using the tool, and inspect with the microscope. The key novelty is vibrating the flower from below while simultaneously inspecting with a microscope from above. Each subsystem is validated via extensive experiments.

BibTex

@article{kong2024towards,
  title={Towards Closing the Loop in Robotic Pollination for Indoor Farming via Autonomous Microscopic Inspection},
  author={Kong, Chuizheng and Qiu, Alex and Wibowo, Idris and Ren, Marvin and Dhori, Aishik and Ling, Kai-Shu and Hu, Ai-Ping and Kousik, Shreyas},
  journal={arXiv preprint arXiv:2409.12311},
  year={2024}
}