Co-emulation of robotics and software-defined radio based 5G wireless communications.

The convergence of robotics and 5G wireless communication technologies has opened new avenues for real-time, dynamic robotic applications. This dissertation introduces a novel framework that integrates the Robot Operating System (ROS), Software-Defined Radios (SDRs), and 5G wireless networks to achieve seamless coemulation of robotic systems. The research emphasizes the unique features of 5G, such as ultra-low latency and high throughput, which enable critical applications like remote surgery, industrial automation, and autonomous vehicles. The methodology combines ROS for robotic control, SDRs for programmable communication channels, and 5G testbeds for high-speed, reliable data transmission. The experimental evaluation focuses on both position-based and velocity-based control systems under varying sampling intervals and mobility scenarios, including drones, cars, and spinning robots. Results highlight the dominance of physical execution delays (displacement delay) over network communication delays, underscoring the significance of hardware constraints in achieving real-time performance. Key findings demonstrate that shorter command intervals improve responsiveness but increase queuing delays, while longer intervals reduce deviation from ideal iv trajectories. The study also explores the impact of environmental factors, mobility patterns, and queuing effects on overall system latency and throughput. This work addresses challenges in scalability, synchronization, and environmental adaptability, offering insights for future integration of 6G technologies. The proposed framework establishes a robust foundation for scalable, multi-robot systems and contributes to advancing the field of robotic teleoperation and autonomous systems in high-speed, low-latency communication networks