This short film documents some of the most innovative projects that emerged from the work of NCCR Robotics, the Swiss-wide consortium coordinated from 2010 to 2022 by EPFL professor Dario Floreano and ETHZ professor Robert Riener, including other major research institutions across Switzerland. Shot over the course of six months in Lausanne, Geneva, Zurich, Wangen an der Aare, Leysin, Lugano, the documentary is a unique look at the state of the art of medical, educational and rescue robotics, and at the specific contributions that Swiss researchers have given to the field over the last decade. In addition to showing the robots in action, the film features extended interviews with top experts including Stéphanie Lacour, Silvestro Micera, Davide Scaramuzza, Robert Riener, Pierre Dillenbourg, Margarita Chli, Dario Floreano.

Nina Wiedemann, Valentin Wüest et al present an efficient and accurate control policy that is trained with the Analytic Policy Gradient method, and experiment with complex aerial robots such as a quadrotor (left). Their controller can track a reference trajectory accurately (right), within a fraction of the runtime required by online-optimisation methods such as MPC (bottom left). In their recent paper, Training Efficient Controllers via Analytic Policy Gradient, Nina Wiedemann, Valentin Wüest, Antonio Loquercio, Matthias Müller, Dario Floreano, and Davide Scaramuzza propose a gradient-based method for control of robotic systems. First authors Nina Wiedemann and Valentin Wüest told us more about their approach, the motivation for the work, and what they are planning next. Our paper is about control for robotic systems, with a focus on aerial vehicles.

Engineers at EPFL have developed a predictive control model that allows swarms of drones to fly in cluttered environments quickly and safely. It works by enabling individual drones to predict their own behaviour and that of their neighbours in the swarm. There is strength in numbers. By flying in a swarm, they can cover larger areas and collect a wider range of data, since each drone can be equipped with different sensors. One reason why drone swarms haven't been used more widely is the risk of gridlock within the swarm.

Drones can do some incredible acrobatics. If you were somehow a passenger on that drone and weren't a trained fighter pilot (and maybe even if you were), you'd pass out and very likely die. Drones don't do a lot of passenger carrying at the moment, which is probably for the best, but we've seen enough crazy ideas to suggest that using autonomous drones instead of autonomous cars to transport humans is probably going to be a reality within a handful of decades.* At the École Polytechnique Fédérale de Lausanne (EPFL), in Switzerland, a group of researchers led by Dario Floreano is already worrying about how we're going to handle personal drone flights, especially in situations where a lot of drones are trying to go in a lot of different directions at the same time. They've come up with an algorithm that allows drones to avoid collisions with each other while also not turning humans into mounds of quivering goo.