Centimeter-Accurate Navigation of Nano-Drones using UWB Technology

Robot vehicle platforms, often called “drones”, offer exciting opportunities for mobile computing applications, as they allow computer systems to actively control the device location for a more efficient and precise interaction with the physical world. While larger drones may weigh more than 1 kg and require a certified operator, nano-drones weigh only tens of grams, are sold as toys, and can be flown by everyone. An example of nano-drone is the Crazyflie, which is open source, weighs ≈ 25 grams only, and has quickly gained popularity in the last years.

We have recently equipped the Crazyflie with an ultra-wideband (UWB) shield on top based on the MDEK 1001, similar to the Loco Positioning system by bitcraze. Such shield allows the Crazyflie to communicate with surrounding UWB devices and obtain accurate distance information. Our goal is to accurately navigate a swarm of Crazyflies through the hallways of our institute, possibly by incorporating UWB-based algorithms and protocols designed in our group, such as SnapLoc. To this end, we have deployed a testbed with more than 50 UWB devices across a hallway as well as a drone cage that can be used to experiment with the Crazyflie.

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Target Group:

  • Students of ICE/Telematics;
  • Students of Computer Science;
  • Students of Electrical Engineering.

Thesis Type:

  • Master Project / Master Thesis

Goals and Tasks:

  • Implement localization techniques based on two-way ranging directly on the Crazyflies;
  • Enrich the Crazyflies with SnapLoc, so to enable a fully-passive localization of nano-drones;
  • Design a hybrid solution making use of the Crazyflie’s embedded crazyradio for communication and of the UWB shield for localization;
  • Fly the nano-drones through the hallway and experimentally measure the localization accuracy that can be achieved with the UWB shield.

Required Prior Knowledge:

  • Knowledge of networked embedded systems;
  • Excellent low-level C programming skills;
  • Basic signal processing knowledge is beneficial;
  • Experience with embedded platforms, UWB technology, and drones is of advantage.


  • a.s.a.p.