Fawky Mohamed developed and delivered the ZED YOLO 3D Node for the ASU-ROAR-Team/ROAR-Autonomous-System repository, focusing on real-time 3D object detection and visualization to enhance autonomous navigation. Leveraging ROS, computer vision, and machine learning, Fawky integrated ZED camera data with the YOLO detection framework, enabling live processing and visualization of objects in three-dimensional space. The solution, implemented in C++ and Python, improved the system’s perception capabilities and established a technical foundation for future enhancements in perception and planning. Over the course of one month, Fawky’s work demonstrated depth in robotics integration and real-time data processing within autonomous systems.