Sniffy Bug: A Fully Autonomous Swarm of Gas-Seeking Nano Quadcopters in Cluttered Environments

We have developed a swarm of autonomous, tiny drones that is able to localize gas sources in unknown, cluttered environments. Bio-inspired AI allows the drones to tackle this complex task without any external infrastructure. In the experiments we used tiny, lightweight and hence very safe Crazyflie drones. We equipped these drones with the appropriate algorithms and hardware to avoid collisions with obstacles and each other, explore the environment, smell gas, and coordinate to efficiently localize the gas source. They do all of this with extremely restricted onboard resources, using a novel, bio-inspired bug algorithm, “Sniffy Bug“, to combine navigation and swarm-based odor source localization. We also introduce a new simulation pipeline that combines indoor environment generation with airflow (OpenFoam) and gas simulation tools (GADEN). This allowed us to learn the best parameters in simulation with an artificial evolution, significantly improving on the manually tuned bug algorithm parameters. Links: