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Autonomus Drones With Novel Sensors And Ultra Wide Band

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Short Description

Autonomous drones deployed in combination with onboard novel sensors (such as short range radar, CMOS optical flow, etc) and wireless sensors can un-lock a host of prospective applications in environments that lack infrastructure communications networks and where access may be impossible for human operators. Community building efforts to engage with this opportunity are hampered by a lack of platform support and an evolving understanding of the performance of known wireless communications systems in dynamic outdoor environments, particularly under mobility. In this project, students will challenge the design of novel drones that can de be designed with a new combination of novel sensors provided by companies like Infineon, STMmicrocoelectronic, and may other, ultra-wide band wake-up radio technologies to enable high-precision and energy-efficient localization of sensors in the field as well as complete autonomous drones. The students will follow the full flow from system design to firmware implementation and they can also deal with machine learning according to the background and the will to learn new topics.

Goal & Tasks

The project(s) will address the following challenges:

  • Investigate and develop techniques and methods to perform autonomuns navigation using novel sensors .
  • The algorithms will be evaluated and optimized for the capability of the processors to increase the energy efficiency ans, at the same increase the response time of the detection
  • A complete hardware and software prototype of drones and smart sensor system, which includes all the subsystems (sensor acquisition, preprocessing, and processing and radio communication), will be developed to demonstrate the benefits of the proposed approach and the capability to achieve low latency and energy efficiency on the challenging scenario of autonomous drones.
  • Indoor Localization using Ultra wide band and unique wake up radio designed in ITET will be used and evaluated by the students.
  • The working prototype with the ARM Cortex-M processors and novel sensors will be evaluated.


(not all need to be met by the single candidate)

  • Knowledge of high and low-level programming languages (e.g. Python, embedded C)
  • Knowledge of embedded systems
  • Basic Knowledge or motivation to learn machine learning and signal processing
  • Motivation to learn how work with sensors provided by companies and even not yet on the market
  • Motivation to build and test a real system and acquiring field data

Detailed Task Description

A detailed task description will be worked out right before the project, taking the student's interests and capabilities into account.

Status: Available

  • Looking for Bachelor Thesis, Semester and Master Project Students
Supervisors: Michele Magno, Tommaso Polonelli


35% Theory and Algorithms
35% Implementation w
30% Data acquisition, Verification, and Testing

IIS Professor

Luca Benini

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Practical Details