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Safety and Efficiency in Robotics: The Control Barrier Functions Approach

Federica Ferraguti, Chiara Talignani Landi, Andrew Singletary, Hsien-Chung Lin, Aaron D. Ames, Cristian Secchi, Marcello Bonfè

2022IEEE Robotics & Automation Magazine71 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

RoboticsComputer scienceEmbeddingRobotArtificial intelligenceControl engineeringControl (management)Simple (philosophy)Code (set theory)Human–computer interactionEngineeringProgramming languageSet (abstract data type)EpistemologyPhilosophySafety Systems Engineering in AutonomySystems Engineering Methodologies and ApplicationsSoftware Reliability and Analysis Research
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