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Showing 1 to 6 of 6 for “"Control Barrier Function"”.
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Safe and Efficient Motion Planning in Robotic Manipulation through Formal Methods
… paths for rigid-body objects; and (2) a learned control barrier function (CBF) tailored for manipulators with multiple degrees of freedom (DoF) and an associated framework CBF-RRT to enable efficient planning for robotic manipulators. Comprehensive experimental results have shown that the …
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Reinforcement Learning Control for Mobile Robot Parking with Safety Constraints
… that combines reinforcement learning (RL) with control barrier function (CBF)-based methods to achieve safe autonomous vehicle control, focusing on parking with obstacle avoidance. We apply Deep Deterministic Policy Gradient (DDPG) methods for continuous control and evaluate policies across …
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A Comparison of Control Methods for Spacecraft Maneuvering With Run Time Assurance
… critical factor in mission completion within the controls field. Controllers designed using data-based approaches like artificial intelligence must uphold the same levels of safety expected from modern controllers, such as Linear Quadratic Regulators. This is accomplished with the application of …
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A Comparison of Control Methods for Spacecraft Maneuvering With Run Time Assurance
… critical factor in mission completion within the controls field. Controllers designed using data-based approaches like artificial intelligence must uphold the same levels of safety expected from modern controllers, such as Linear Quadratic Regulators. This is accomplished with the application of …
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Safe and adaptive reinforcement learning for robotics applications
In recent years, learning-based control methods, especially those leveraging the power of reinforcement learning (RL) and deep learning, have demonstrated impressive performance in complex robotics control tasks. However, they often suffer from the lack of safety and robustness guarantees, which …
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SAFE REINFORCEMENT LEARNING-BASED GREEN LIGHT OPTIMAL SPEED ADVISORY FOR MIXED-TRAFFIC PLATOONS
… during implementation. Third, we integrate Control Barrier Functions (CBFs) into the RL-based policies to ensure car-following and red-light safety. Fourth, we address signal timing undertainty by leveraging CP to estimate a confidence interval of the signal timing prediction results. We …