The MAV-lab performs research in several areas:

Autonomous flight of Micro to Nano Air Vehicles

Paparazzi Lisa-S Autopilot

The challenges in autonomous flight of MAVs derive from the stringent weight and power requirements of MAVs. For example, the DelFly II flapping wing MAV weighs around 16 gram, including battery, sensors, and processing. In the same time, MAVs move rather quickly and have to respond in real time to their environment in order to navigate and explore unkown environments.

  • Fully autonomous flight of MAV below 20 grams
  • Control of hybrid MAV (= blend of fixedwing + rotorcraft)
  • Trained or adaptive control strategies

Collision Avoidance

Indoor Stereo-Vision

Collaborative avoidance, vision-based avoidance, acoustic avoidance, collision-avoidance algorithms but also inherently safe designs are expected to play a crucial role in the integration of Micro Air Vehicles in the national airspace. Collision avoidance and inherent safety form a red line through the research at the MavLab.

  • Vision-based interaction with the world
  • Hear & Avoid
  • Inherently Safe Design

Design and aerodynamics of MAVs

Aerodynamics of Flapping Wings

Especially the smaller MAVs operate in low Reynolds conditions. This means that unsteady aerodynamic effects play a larger role. Since these effects are less well understood than the steady aerodynamics in a traditional aircraft setting, research is necessary to better understand what is happening, and to better predict how an MAV design will behave. In this research area, we focus on special MAV designs, such as flapping or morphing wing MAVs.

  • Flapping wings
  • Morhping wings
  • Low Reynolds Numbers
  • Unsteady Flow

MAV operations

Air Traffic Control

MAVs are relatively new to the air space. For real-world applications, MAVs have to be operated in a safe manner. Of course, the smallest and lightest of MAVs are inherently safe by their low mass and their structure (think of the DelFly). Nonetheless, for slightly larger MAVs, active safety is required, typically referred to as “sense-and-avoid”. In this area we study an MAV system as a whole, which means that we do not only look at the MAV, but also the human operator(s) and the context (including surrounding buildings and other air traffic). Some specific topics include hear-and-avoid and single-operator control of a swarm of MAVs.

  • Operator – Vehicle interaction
  • Swarming
  • Risc Managment
  • Mission Control