AI Driven Threat Detection for Autonomous Robots
Sher Taj, Zahid Ullah Khan, Sareer Ul Amin, Shantanu Awasthi, Muneer Khan, Jagjot Bhardwaj · Advances in computational intelligence and robotics book series · 2025
As autonomous robots become more prevalent in diverse industries, they substantially increase productivity and safety. Still, these robots commonly have a passive role in complex and dynamic areas, which means they are exposed to many possible threats. Besides these security risks, cyber-attacks against damaged software, unreliable wall and hardware failures, and sensor issues are some problems they can face. These problems figure the creation of a successful threat detection system that is the only possible solution to make sure the autonomous robots can operate safely and correctly. This chapter is about the safety of the robots by using Artificial Intelligence (AI), the part that is most pivotal for the entire security. We explore the ways in which AI models such as Machine Learning (ML), Deep Learning (DL), computer vision, and anomaly detection enable machines to accurately identify and react wisely to possible threats.