Challenges in machine learning for automation
Priyanka Kaushik, Premanand Singh Chauhan, Arvind Singh Rawat · 2025
This chapter critically examines the integration of machine learning (ML) in robotic automation, highlighting the substantial challenges that must be addressed to unlock the full potential of autonomous robots. We explore how ML enhances perception, control, real-time decision-making, and adaptability in robotics, while also confronting issues such as data requirements, interdisciplinary collaboration, and ethical implications. Emerging methods in transfer learning, edge computing, and explainable AI are discussed as future directions to mitigate these challenges, offering a blueprint for continued progress in autonomous robotics.