Christophe De Wagter

About

Christophe De Wagter is a pioneering robotics researcher whose work sits at the intersection of bio-inspired flight, micro air vehicles (MAVs), and autonomous navigation. Based at Delft University of Technology, he has made landmark contributions to flapping-wing robotics through the celebrated DelFly project, helping transform insect-inspired flight from a conceptual curiosity into a functional autonomous platform. His 2018 study on a tailless aerial robotic flapper — garnering over 419 citations — revealed fundamental insights into how flies execute rapid banked turns through torque coupling, bridging biology and engineering in a genuinely novel way. De Wagter has also championed swarm robotics, authoring influential work on enabling tiny flying robots to collaboratively explore unknown indoor environments with minimal navigation hardware, accumulating over 266 citations. His broader contributions span optical flow-based control, autonomous drone racing, onboard stereo vision for ultra-lightweight platforms, and attitude estimation inspired by insect sensory systems. With a portfolio exceeding 1,200 citations across diverse but coherent themes, De Wagter exemplifies the rare researcher who advances both theoretical understanding of biological flight and the practical engineering of the world's smallest autonomous flying machines.

Research Focus

Key Achievements

Top Papers

1. 1
   A tailless aerial robotic flapper reveals that flies use torque coupling in rapid banked turns

   419 citations · 2018
2. 2
   Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment

   266 citations · 2019
3. 3
   Design, aerodynamics and autonomy of the DelFly

   211 citations · 2012
4. 4
   A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints

   124 citations · 2020
5. 5
   Autonomous flight of a 20-gram Flapping Wing MAV with a 4-gram onboard stereo vision system

   119 citations · 2014
6. 6
   The DelFly

   74 citations · 2015
7. 7
   Enhancing optical-flow-based control by learning visual appearance cues for flying robots

   64 citations · 2021
8. 8
   Visual model‐predictive localization for computationally efficient autonomous racing of a 72‐g drone

   46 citations · 2020
9. 9
   Accommodating unobservability to control flight attitude with optic flow

   42 citations · 2022
10. 10
    Optic-Flow Based Slope Estimation for Autonomous Landing

    39 citations · 2013

Key Collaborators

Contact & Links