This article aims at presenting an introductory overview of the theoretical framework of control barrier functions (CBFs) and of their application to the design of safety-related controllers for robotic systems. The article starts by describing the basic concepts of CBFs and how they can be used to build optimization problems embedding CBF-based constraints, whose solutions correspond to the control input enforcing the desired safety properties into the behavior of the controlled system. Simple examples, understandable for readers with a basic background in control theory and accompanied with source code for their simulation, are used to highlight the appealing features of the CBF-based approach. Then, more complex formulations applicable to robotic manipulators are introduced, recalling recent literature results allowing users to implement a robust design methodology. Finally, it is shown that CBFs are suitable for the implementation of safe human–robot collaboration in a realistic industrial scenario by means of the experimental validation in an industrial setup for collaborative robotics.
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