Built an automation module for a RC Plane company

Developed an autonomous flight module using Ardupilot that enables fully automated flight operations for passenger and cargo flights. This module incorporates flight planning, safety measures based on SAEISS guidelines, payload management, and automated take-off and landing procedures. The system ensures adherence to flight conditions and provides real-time decision logging with accompanying visual snapshots.

Skills: Programming, Ardupilot, Testing and Validation, Image Processing, Flight Planning and Navigation, ROS, Unreal Engine, UAV Systems

Tools: ROS, XFLR5, Unreal Engine, OpenCV

Key Features:

Flight Planning: The module allows the client to input a flight path, considering factors such as weather conditions, air traffic, airspace restrictions, and fuel efficiency. It optimizes routes and calculates the most efficient flight paths, waypoints, and altitudes based on the provided parameters.

Safety Measures: Adhering to the SAEISS guidelines, the module integrates safety features such as collision avoidance systems, redundancy in critical components, and fail-safe mechanisms. It continuously monitors flight conditions, assesses risks, and takes appropriate actions to ensure the safety of the aircraft and its occupants.

Payload Management: For cargo flights, the module incorporates payload management capabilities. It enables the client to input payload details, and the system verifies if the payload falls within the preset range. This ensures safe and stable flight operations by considering factors such as weight distribution, load limits, and center of gravity calculations.

Real-time Decision Logging: Every decision made by the autonomous flight module is logged in real-time. The system records crucial information such as flight parameters, detected obstacles, navigation adjustments, and safety actions taken. Additionally, the module captures a visual snapshot at the time of each decision, providing a comprehensive log for post-flight analysis.

Automated Take-off and Landing: The module fully automates the take-off and landing procedures. It utilizes precise control algorithms, accounting for wind conditions, runway length, and obstacle detection. The automated system communicates with air traffic control, adhering to established protocols to ensure safe and efficient take-offs and landings.

Success Rates: The developed module showcases exceptional success rates, with a 95% success rate for take-offs and a 98% success rate for landings. These high success rates demonstrate the system's reliability and capability to handle critical flight phases autonomously.

Conclusion: The autonomous flight module developed for passenger and cargo operations offers a comprehensive solution for fully automated flights. By integrating flight planning, safety measures, payload management, and automated take-off and landing procedures, this module enables efficient and safe autonomous operations. The real-time decision logging and visual snapshots provide valuable data for analysis and performance evaluation.