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
Objectives
- Platform Redesign: Revise the current quad-copter platform to enhance its design and
functionality - 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
Deliverable
- 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
- Detailed documentation outlining modifications made to improve the quad-copter
- Anemometer Integration System:
- Fully functional setup, integrating the existing anemometer with the quad-copter
platform - Documentation detailing the integration process, including circuit diagrams, wiring
configurations, and software interfaces
- Fully functional setup, integrating the existing anemometer with the quad-copter
- 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
Network
- Analysis report of the comparison of the trajectory estimated using the Dynamic
Contact
Kenneth Joseph Paul, Jan Skaloud