This thesis is focused on developing a safe collaborative framework for compliant industrial manipulators. Industrial manipulators have been a cornerstone of modern industry for several decades. They are characterized by their precision, repeatability, and high payload capacity. However, they have very limited flexibility in terms of programming and deployment. For this reason, they are typically found in large-scale industries. On the other hand, as industries evolve and labor shortages become more prevalent, there is a growing need for robots to enter smaller-scale operations and handle delicate tasks that require adaptability and compliance in direct interaction with the environment. This is where collaborative robots have emerged as a promising solution. While collaborative robots offer features that enable soft contact and safe human-robot interaction, off-the-shelf models often lack the precision, repeatability, payload capacity, and reach required by industrial applications. To bridge this this gap, the goal of this thesis is to develop a collaborative framework that combines the strengths of both industrial and collaborative manipulators. By integrating compliant behaviour into industrial manipulators, we aim to enable safe interaction with humans and adaptability to dynamic environments, while retaining the precision, repeatability, and payload capacity essential for industrial tasks. Through this endeavor, we seek to enhance the versatility and applicability of manipulator systems across a wide range of industrial settings.