This article presents a comprehensive review of control approaches for industrial robotic manipulators, focusing on research conducted from 2020 onwards. The efficient functioning of robotic arms and successful task completion necessitate effective control strategies. Addressing real-world challenges, such as dynamic system variations due to environmental changes and unknown disturbances, remains crucial. To tackle these challenges, robust control strategies, including PID, H∞, and Model Predictive Control, are thoroughly surveyed. Commercially employed trajectory planning techniques for manipulators are also extensively discussed. The issue of chattering in control systems is highlighted, and various methods to mitigate it are presented. Ultimately, the paper concludes by providing valuable insights into prospective areas for future research, with the aim of enhancing the capabilities and performance of control strategies for industrial robotic manipulators. This study offers valuable knowledge to advance the field of robotic automation in Industry 4.0, fostering the development of efficient and intelligent manufacturing processes.