This project was started in , electronics and control loops. Because I always need a cool project to learn new things, it was clear that something that can fly had to be built.
The project started as a "tricopter-only" project, but as I wanted to build smaller vehicles with more payload capacity, I decided to make some quadrotor, hexacopter and Y6 hexacopter firmwares too. My main interest is to build very small MAVs that fly as good as larger ones (or even better) and that can be controlled by wireless video link. I also experimented with autonomous flight in GPS-denied areas (video), and with GPS assisted autonomous hover (video).
-- William

Contact: Shrediquette @ g m x . d e --- All content published under CC Attribution-Noncommercial-Share Alike 3.0 Germany

2nd place in the IMAV 2014 competition!

This year, the 'International Micro Air Vehicle Conference and Flight Competition' (IMAV2014) took place on the 13th of August in the Netherlands. I am very happy to announce that together with my team (called 'Dipole', consisting of Prof. Klaus-Peter Neitzke, Dr. Hans-Peter Thamm and me = William Thielicke), we won the second prize in the IMAV competition!

Fifteen international teams accepted the challenge and tried to score points in the simulation of a major natural disaster inside a small artificial village. Several tasks had to be solved during a 30 minute time slot: Creating a stitched orthophoto of the whole village; flying through the village and identifying house numbers and survivors inside the houses; observing a given spot; entering a two-storeyed house and flying through the rooms while identifying objects in the rooms (see the detailed rules here). Points were awarded for each of these tasks, and summed for the final score.

Our team used three different multirotors in parallel, including my 'GEMiNi' hexrotor, an 'Alpha' quadrotor by Klaus-Peter Neitzke and the larger 'Geocopter' by Hans-Peter Thamm. This year, the 'Alpha' and the 'GEMiNi' were again the smallest vehicles of the competition. While the 'Geocopter' flew over the village autonomously creating a high-resolution orthophoto, the 'Alpha' and 'GEMiNi' went through the houses of the village to identify some house numbers. This was pretty challenging, because we had to use 5.8 GHz for the video link, and there were a lot of obstacles between the antennas, making the video quality very poor. These copters also entered a large house and flew through many rooms. This was not as easy as I thought, as there was a strong wind that was clearly noticeable also inside the house (because the windows were open). The space in the rooms was very limited, and we didn't know anything about the floor plan and potential obstacles before we entered the building.

The first prize went to the team of the National University of Singapore. They came with eighteen people and ten copters. Most of these copters were equipped with impressive laser range finders and other fancy sensors. This team really deserved the first prize, they did a great job!

Here's the scoring of the first three teams, the scoring of the other teams can be found here.

1st prize 

National University of Singapore (Singapore) points: 683
Onboard automatic image stitching, onboard number recognition(*), onboard autonomous laser-based room navigation, onboard computer vision based precision roof landing, autonomous takeoffs, autonomous landings (*), onboard computer vision based 7-segment digit recognition (*), autonomous flying WiFi-relay.

2nd prize 

Team Dipole (Germany) points: 425
Smallest MAV's of the competition. Very talented FPV flight with many take-off, precision landings, reading house numbers, visiting 18 indoor rooms (several double and not counted), recognizing 16 indoor objects correctly. Geocopter auto-take-off and flight, precision auto landing and partial high resolution ortophoto.

3rd prize 

Ecole Nationale de l'Aviation Civile (France) points: 189
Autonomous takeoff, Best overall photomission, all blockades visible, full village high resolution map at 6cm/pixel, autonomous computer vision based 7-segment display reading (**), longest correct observation string, autonomous roof landing (*), reading house numbers with many ARdrones in autonomous flight. Several autonomous landings.

(*) Item attempted but either failed, or needed manual flight, or not according to competition rules.
(**) Item attempted in autonomous mission mode, but human intervention was needed and it got scored in autonomous flight mode.

Here are some photos of the event:

The GEMiNi entering a building
Klaus-Peter and a judge
Award ceremony
The trophy
NUS UAV Research group (1st place, Singapore)
NUS UAV Research group (1st place, Singapore)
Williams FPV flight
Location of the competition
I would like to thank the organization committe, it was really great fun - again! We're looking forward to next year in Aachen!


  1. Congratulations,

    cannot wait to see some ... impressions :)

  2. This comment has been removed by the author.

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