In recent history, Nasa and ESA, among other agencies, have been analyzing two priorities of present and future long term missions in space: the reduction of the teams’ workload, and the food supply.

ISAE-SUPAERO (France)

This project tackles these issues by proposing an autonomous efficient growing plant systems based on arugula. Using a nutrient filled hydroponic technique, an arm robot, the image recognition algorithm Overfeat, OpenCV, Python-tesseract and a Markov Decision Process environment, decisions will be taken in order to minimize resources consumption and the amount of space taken. A prototype will be constructed and the algorithms tested and optimized. The second stage of the project will consist in analyzing a greater amount of plants as well as isolating the system from ambient conditions.

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Setup of a plant growing system, with the goal of testing growing strategies with A.I. (with uncertainty and machine learning). In fact, plant growing is a repetitive and time-consuming task, which can be automated to some extent, saving space, optimizing resources and reducing pesticide use.

ISAE-SUPAERO (France)

Implementation on real robotic systems (e.g. sensors and actuators) is pursued, with the following main goals:

  1. complete a state of the art of vegetable growing systems, given the constraints identified,
  2. propose a prototype (e.g. https://farm.bot/),
  3. propose an experimental setup and implementation (graphical interface, data recording, etc.), and
  4. optimize and deploy growing strategies for the platform.

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Development of antennas, supported by the Astre’nogs association, that will be part of an open source global network of satellite ground-stations named SatNOGS and made available to the scientific community. The final outcome is an antenna what can receive both UHF and VHF frequencies.

ISAE-SUPAERO (France)

Download the document here.