首页|Data on Robotics Discussed by Researchers at University of Michigan (Advances In the Theory of Control Barrier Functions: Addressing Practical Challenges In Saf e Control Synthesis for Autonomous and Robotic Systems)
Data on Robotics Discussed by Researchers at University of Michigan (Advances In the Theory of Control Barrier Functions: Addressing Practical Challenges In Saf e Control Synthesis for Autonomous and Robotic Systems)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ro botics. According to news reporting originating from Ann Arbor, Michigan, by New sRx correspondents, research stated, “This tutorial paper presents recent work o f the authors that extends the theory of Control Barrier Functions (CBFs) to add ress practical challenges in the synthesis of safe controllers for autonomous sy stems and robots. We present novel CBFs and methods that handle safety constrain ts (i) with time and input constraints under disturbances, (ii) with high-relati ve degree under disturbances and input constraints, and (iii) that are affected by adversarial inputs and sampled-data effects.”
Ann ArborMichiganUnited StatesNort h and Central AmericaEmerging TechnologiesMachine LearningRoboticsRobotsUniversity of Michigan
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