Fully Autonomous Swarm of Gas-Seeking Nano Quadcopters

Fully Autonomous Swarm of Gas-Seeking Nano Quadcopters – Link

Source: UAS Vision

Article Headlines
  • Researchers from TU Delft (the Netherlands), University of Barcelona, and Harvard University have now developed the first swarm of tiny drones that can autonomously detect and localize gas sources in cluttered indoor environments.
  • The main challenge the researchers needed to solve was to design the Artificial Intelligence for this complex task that would fit in the tight computational and memory constraints of the tiny drones. They solved this by means of bio-inspired navigation and search strategies. The scientific article has now been made public on the ArXiv article server, and it will be presented at the IROS robotics conference later this year. The work forms an important step in the intelligence of small robots and will allow finding gas leaks more efficiently and without the risk of human lives in real-world environments.
  • Autonomous gas source localization is a complex task. For one, artificial gas sensors are currently less capable than animal noses in detecting small amounts of gas and staying sensitive to quick changes in gas concentration. Moreover, the environment in which the gas spreads can be complex. Consequently, much of the research in this area has focused on single robots that search for a gas source in rather small, obstacle-free environments in which the source is easier to find.
  • The development of this type of technology to a fully functioning product still requires further work. For instance, the current work does not yet tackle moving in three dimensions to locate gas sources at a height. Furthermore, the robustness of navigation should also be improved before deploying the drones in a real emergency scenario.
  • However, the current work is very promising. The developed algorithms are not only useful for detecting gas leaks in buildings, but also for scientific missions such as detecting methane on Mars or economical use such as the early detection of diseases or pests in greenhouses.
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