VRTDrone - Hybrid VTOL Drone for Autonomous Sports Tracking

Summary

The VRTDrone team has been tasked with designing, manufacturing, and implementing a vertical takeoff and landing (VTOL) capable of autonomous flight in urban and confined environments. This project looks to address a need for a small aerial system capable of operating safely and reliably in confined or urban environments and support sports object-tracking-related tasks with minimal burden imposed on the operator.

Analyzing sport gameplay often requires expensive tracking systems or manually operated cameras, limiting access for amateurs. As a result, many players and coaches lack affordable tools that can help to capture and analyze their respective sports during games and practices.

This drone could make game analysis much more accessible and efficient that currently possible helping users gain deeper insight into their matches. The primary groups affected include players, coaches, and analysts at an amateur level where professional tracking systems are often unavailable.

The scope of this project focuses on designing and integrating the aerial platform, onboard sensors, AI tracking software, and demonstrating the systems' ability to successfully track a soccer ball during testing.

Technical Approach/Methodology

To address the need, we are developing an aerial system that can automatically detect and track a soccer ball from above. The system uses a small aircraft capable of two modes of flight with a camera and onboard computing hardware to observer the field and analyze video in real time.

Computer vision algorithms will be used to identify the soccer ball within the camera’s video feed and determine its position on the field. This information is then processed by onboard software that allows the aircraft to maintain a clear view of the ball while it moves. By combining object detection with flight control systems, the platform can continuously track the ball without requiring manual camera operation.

Key technologies used in this project include AI based object detection, onboard sensors, and embedded flight control systems. This system is being developed using publically available robotics and programming tools which allow for the drone to process visual data and adjust its position accordingly.

Outcomes

By the end of this project, we will produce a functional prototype of an aerial tracking system capable of autonomously detecting and tracking a soccer ball from an aerial perspective. The system will integrate a VTOL aircraft platform, onboard camera, computer vision software, and flight control components to demonstrate real-time ball tracking during flight.

Key deliverables include the designed and assembled aerial platform, the developed computer vision algorithm used to detect and track the soccer ball, and the integrated control system that enables the aircraft to maintain an optimal viewing position. The project will also include flight test demonstrations that validate the system’s ability to track a moving ball in a controlled environment.

Additional deliverables will include technical documentation, system design reports, and recorded test results that summarize the development process and performance of the prototype. Together, these outcomes demonstrate the feasibility of an autonomous aerial tracking system for sports analysis and provide a foundation for future improvements and applications.

Project Media

Project Poster