Hybrid Drone-Bot Control System
An innovative graduation project featuring both aerial and ground vehicles with AruCo marker recognition, autonomous navigation, and intelligent command processing for coordinated multi-platform operations.
About the Project
Developing a hybrid autonomous system combining aerial drone and ground robot with AruCo marker recognition and intelligent command processing
Dual Platform System
Integrated aerial drone and ground robot working in coordination, each capable of autonomous navigation and task execution with seamless communication between platforms.
AruCo Marker Recognition
Advanced computer vision system capable of detecting, identifying, and processing AruCo markers for navigation commands, positioning, and task coordination.
Intelligent Command Processing
Real-time command interpretation system that processes visual markers and executes movement commands like forward, backward, turn, and complex maneuvers.
System Specifications
Meet Our Team
The dedicated three-person team behind this innovative hybrid drone-bot system and our supervisor.
Özgür ERKENT
Project Supervisor
Served as the academic supervisor of the project, providing guidance on system architecture, integration strategies, and research methodology. Ensured the project's alignment with academic standards and supported the team through all development phases.
Berkehan ORHON
Team Member
Expert in computer vision and image processing. Developed the AruCo marker detection system and command interpretation algorithms for both drone and ground robot platforms.
Buğra TEKTEPE
Team Member
Specialized in software development and system integration. Played a key role in merging drone hardware components with control software, ensuring seamless operation. Contributed to the development of autonomous behavior logic and inter-platform coordination.
Eda YÜCE
Team Member
Focused on the development of the wheeled ground robot, primarily handling its software systems. Responsible for implementing motion control, sensor integration, and communication interfaces. Contributed to building a reliable and responsive ground navigation system.
Project Outcomes
Explore our research findings, demonstrations, and downloadable resources from the hybrid drone-bot system
Research Poster
Comprehensive visual presentation of our hybrid drone-bot system methodology, AruCo marker integration, and experimental results.
Demo Video
Watch both drone and ground robot in action demonstrating AruCo marker recognition, command processing, and coordinated autonomous operations.
Source Code
Complete source code repository including drone control, ground robot systems, AruCo detection algorithms, and command processing modules.
Project Photos
Visual documentation of our hybrid drone-bot system development process, testing phases, and final demonstrations showcasing both platforms in action.
Project Photo Gallery
Get in Touch
Have questions about our hybrid drone-bot project? Want to collaborate or learn more about our AruCo marker system and autonomous coordination research? We'd love to hear from you.
hacettepeliadimopter@gmail.com
University
Hacettepe University Computer Science Department
Project Timeline
Research & Planning
September 2024
Hardware Design & Assembly
October 2024 - January 2025
AruCo Based System Development
January 2025 - March 2025
Platform Integrations
April 2025
Testing & Validation
May 2025
Documentation & Presentation
June 2025