Small, light-weight flying robots such as the 20-gram DelFly Explorer form an extreme challenge to Artificial Intelligence, because of the strict limitations in onboard sensors, processing, and memory. I try to uncover general principles of intelligence that will allow such limited, small robots to perform complex tasks.
Vision is a prime sense for both animals and robots. I create efficient vision algorithms for robot control and navigation.
Fruit flies are able to fly, avoid obstacles, navigate, and socially interact with each other with only a 100,000 neurons. Insects are a rich source of inspiration for elegant, efficient AI.
As Rodney Brooks said: "Simulation is doomed to succeed" - I focus on problems actually faced by robots in the real world.
Please click below to have a look at a selection of my current research projects.
Optical flow for small flying robots Flying insects heavily rely on optical flow for visual navigation and flight control. Roboticists have endowed small flying robots with optical flow control as well, since it requires just a tiny vision sensor. However, when using optical flow, the robots run into problems that insects appear to have overcome. […]
On December 6, 2019, the MAVLab team won the AI Robotic Racing (AIRR) world championship, taking home 1 Million dollars in prize money! The AIRR competition was an autonomous drone race season set up by Lockheed Martin and the Drone Racing League, aiming to push the boundaries of AI for robotics. Whereas typically autonomous drones […]
We have succeeded in making a swarm of tiny drones that can autonomously explore unknown environments. This achievement, published in Science Robotics on October 23, is a result of a 4-year collaboration with researchers from the University of Liverpool and Radboud University of Nijmegen. The main challenge was that the tiny 33-gram drones need to […]