news    views    podcast    learn    |    about    contribute     republish    

Bart Duisterhof


Homepage

I am a motivated and experienced student in the field of autonomous aerial robots, keen to contribute to the field by enabling the next generation of fully autonomous robots. My interests lie in applying hardware-software co-design to execute expensive algorithms within strict resource constraints. So far, my research has focused on fully autonomous flight of the DelFly Nimble and deep reinforcement learning-based navigation of a stock CrazyFlie.



A commonly shared dream by engineers and fire & rescue services, would be to have swarms of such drones help in search-and-rescue scenarios, for instance to localize gas leaks without endangering human lives. Tiny drones are ideal for such tasks, since they are small enough to navigate in narrow spaces, safe, agile, and very inexpensive. In this article, we show how we tackled the complex problem of swarm gas source localization in cluttered environments by using a simple bug algorithm with evolved parameters, and then tested it onboard a fully autonomous swarm of tiny drones.