Autonomous Systems

Autonomous Systems are sophisticated entities designed to operate in complex environments with little to no human oversight. These systems rely on the convergence of Artificial Intelligence, Machine Learning, and Robotics. By processing inputs from Sensors such as LiDAR and Radar, they can interpret their surroundings in real-time.

The development of Self-Driving Cars represents a significant milestone in this field, utilizing Computer Vision to identify obstacles. Industry standards provided by SAE International (sae.org) categorize the levels of autonomy from driver assistance to full automation. Furthermore, Unmanned Aerial Vehicles (UAVs) are increasingly used for logistics, as highlighted in technical reports by NASA (nasa.gov). These Cyber-Physical Systems must also address critical issues in Cybersecurity to prevent unauthorized access.

To ensure reliability, researchers are focusing on Explainable AI and the integration of Edge Computing to reduce decision latency. The synergy between Control Theory and data-driven models remains a primary area of academic inquiry.

• Edge Computing
• Computer Vision
• Control Theory
• Internet of Things