Revolution on the Road: Optimizing Resource Management and Improving Perception Models in Autonomous Vehicle Systems

The emergence of autonomous vehicles (AVs) represents a crucial breakthrough in robotics, ushering in a new era of transportation. Despite their increasing adoption, AV systems often need more robustness in their functionality. The need for more thorough documentation on the technology behind these vehicles makes it challenging to understand and analyze them. This lack of transparency, especially regarding the hardware used, showcases tremendous obstacles for Machine Learning applications aiming to take the most advantage of these systems. This work's goal is to get in detail with one of the crucially important components in modern AV and robotics applications: the Jetson AGX Orin. By organizing an thorough analysis study, this paper aims to show the capabilities and limitations of this device within multiple robotics applications. By providing a more detailed understanding of this critical hardware device, we are on the path to significantly improve the reliability and effectiveness of AVs.