Micro Air Vehicle Laboratory, Delft University of Technology, Delft, South Holland, Netherlands

[Administrator]

Website - mavlab.tudelft.nl

youtube.com/microuav

twitter.com/microuav

Projects:

Sniffy Bug

delftAcopter, full electrically powered rescue hybrid drone

DelFly, autonomous flapping wing MAV (Micro Air Vehicles)

 

[Administrator]

IMAV 2011 Summer Edition Talks

Published on Aug 6, 2014

 

[Administrator]

Seeing distances with one eye

Published on Jan 7, 2016

A new theory allows drones to see distances with a single camera. Drones approaching an object with an insect-inspired vision strategy become unstable at a specific distance from the object. Turning this weakness into a strength, drones can use the timely detection of that emerging instability to estimate distance. The new theory will allow for further miniaturization of autonomous drones and provides a new hypothesis on flying insect behavior.

Article: "Monocular distance estimation with optical flow maneuvers and efference copies: a stability-based strategy.", by G.C.H.E. de Croon, in Bioinspiration & Biomimetics, 2016.

Article "New insect-inspired vision strategy could hasten development of mini-drones"

by Guido de Croon
January 7, 2016

 

[Administrator]

A drone inside everybody's pocket: Bart Remes at TEDxAmsterdam

Published on Nov 6, 2013

Bart Remes predicts that everyone who now has a phone in their pocket in five years from now will have a drone in there as well. Bart shows the audience how his drone works and predicts how we will use them in the future.

Bart Remes is a project manager of the micro aerial vehicle lab at the aerospace faculty of the TU Delft. When he started 19 years ago with the activities on small drones, nobody believed in the future of these small devices. Now 10 years later the micro aerial vehicle lab of the TU Delft has a central spot in the activities of the aerospace faculty. The research that is done at the lab has international high prestige and is unique in the world.

 

[Administrator]

Computationally efficient autonomous racing of a 72-gram drone

Published on May 27, 2019

We present a tiny autonomous racing drone, weighing only 72 grams. This tiny drone uses very efficient algorithms for onboard vision, state estimation and control in order to fly a (quite narrow) drone racing track with on average 2 m/s (peaks of 2.7 m/s). This speed is on a par with much larger, state-of-the-art autonomous racing drones.

The key idea behind our approach is not to perform generic, but computationally expensive, visual inertial odometry. Instead, the drone relies on model predictions, which are corrected by means of visual localization with the help of gate detections.

The details are described in the article "Visual Model-predictive Localization for Computationally Efficient Autonomous Racing of a 72-gram Drone." - submitted.

"World's smallest autonomous racing drone created by Dutch scientists"

by Nick Lavars
May 30, 2019

 

[Administrator]

Article "A swarm of autonomous tiny flying robots"

by Guido de Croon
November 4, 2019