Quad-copter based wind estimation experimental platform

Quadcopter + Anemometer setup

This project is already taken

The project focuses on designing an experimental platform leveraging quad-copters to estimate wind. It encompasses redesigning an existing platform, creating a system for integrating an anemometer for synchronized data logging with GPS time, executing test flights, and comparing flight trajectory estimations using Dynamic Network algorithms with a known solution


  • Platform Redesign: Revise the current quad-copter platform to enhance its design and
  • Anemometer Setup: Develop a robust system that utilizes an existing anemometer to
    accurately measure wind. Synchronize data logging with GPS time to ensure precise
    correlation between wind conditions and the quad-copter’s flight trajectory
  • Test Flights: Execute a sequence of test flights to validate the newly implemented system
    and gather data for sensor fusion
  • Dynamic Network Comparison: Use the collected data to perform sensor fusion using
    Dynamic Network and compare it to a known solution. This will help to validate and ensure
    the accuracy and reliability of the collected data from the platform


  • Enhanced Quad-copter Platform:
    • Detailed documentation outlining modifications made to improve the quad-copter
      platform’s design and functionality
    • Revised schematics or blueprints showcasing the updated quad-copter structure and any
      added components
  • Anemometer Integration System:
    • Fully functional setup, integrating the existing anemometer with the quad-copter
    • Documentation detailing the integration process, including circuit diagrams, wiring
      configurations, and software interfaces
  • Test Flight Data:
    • Comprehensive data-set containing recorded data from test flights performed
    • Supplementary data specifying wind conditions, geographical locations, and dates of the
      conducted flights
  • Sensor Fusion Analysis Report:
    • Analysis report of the comparison of the trajectory estimated using the Dynamic


Kenneth Joseph Paul, Jan Skaloud