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A robotised platform for full-cycle greenhouse growth. We built the real-time machine learning computer vision that diagnoses plants from a 25-channel industrial camera.
AgriTech · Robotics & computer visionA robot for every stage of the greenhouse.
The goal of this project was to develop a robotised platform for full cycle greenhouse growth. The platform is capable of a fully automated planting and germination process, transfer of the sprouts to the soil in the greenhouse, monitoring of the growth process and state of ripeness, life video diagnostics and disease/pest prevention, harvesting and sorting of the crop.
The system was composed of mechanisms for movement and manipulation of plants, sprouts and crops; a computer vision module for navigation, diagnostics and 3D space mapping (SLAM); and a cloud based controlling module and storage of sample pictures and 3D space points for full transfer of knowledge between robots/systems. The onboard ROS Linux provided the needed low and high level controls of the platform.
Full growth cycle Planting and germination Transfer of sprouts to the soil Growth and ripeness monitoring Disease and pest prevention Harvesting and sorting Onboard ROS Linux Computer vision · SLAM · CloudDiagnosing plants in real time, on board.
The challenge of the project was the on-board real time machine learning algorithms for diagnostics of the plants using a 25 channel industrial camera, which can categorize:
01The ripeness of the crop (onboard, real time)
02Health conditions of the entire plant: leaves, fruit and stems (onboard, real time)
03Nutrient deficiency (onboard, real time)
04Lighting conditions through the day (cloud based)
Computer vision for the whole greenhouse.
The client assigned Generic Soft with the machine learning computer vision algorithms for real time segmentation and classification of the video stream of high channel industrial camera. Based on the classification, our team developed functionality for:
Location of individual plants and their parts
Growth rates of individual plants and overall statistics
Regions of infection/infestation
