Research of control methods for a mobile manipulation robotic platform within the framework of industry 5.0 concepts

Abstract

The paper considers current methods of controlling a mobile robotic manipulation platform in the context of implementing Industry 5.0 concepts, which envisage the integration of humans and robots into a single collaborative production environment. The research focuses on analyzing the possibilities of applying predictive control models, impedance strategies, and machine learning methods to achieve adaptability, flexibility, and safe interaction with the operator in dynamic conditions. The feasibility of using hybrid control architectures that combine the reliability of classical approaches and the intelligence of modern algorithms is substantiated. The results emphasize that effective control of mobile manipulation platforms is the key to creating innovative, human-centered production systems that comply with Industry 5.0 principles.