Control barrier functions: Theory and applications
This paper provides an introduction and overview of recent work on control barrier functions
and their use to verify and enforce safety properties in the context of (optimization based) …
and their use to verify and enforce safety properties in the context of (optimization based) …
Learning control barrier functions from expert demonstrations
Inspired by the success of imitation and inverse reinforcement learning in replicating expert
behavior through optimal control, we propose a learning based approach to safe controller …
behavior through optimal control, we propose a learning based approach to safe controller …
Robust control barrier–value functions for safety-critical control
This paper works towards unifying two popular approaches in the safety control community:
Hamilton-Jacobi (HJ) reachability and Control Barrier Functions (CBFs). HJ Reachability has …
Hamilton-Jacobi (HJ) reachability and Control Barrier Functions (CBFs). HJ Reachability has …
Advances in the Theory of Control Barrier Functions: Addressing practical challenges in safe control synthesis for autonomous and robotic systems
This tutorial paper presents recent work of the authors that extends the theory of Control
Barrier Functions (CBFs) to address practical challenges in the synthesis of safe controllers …
Barrier Functions (CBFs) to address practical challenges in the synthesis of safe controllers …
Runtime assurance for safety-critical systems: An introduction to safety filtering approaches for complex control systems
More than three miles above the Arizona desert, an F-16 student pilot experienced a gravity-
induced loss of consciousness, passing out while turning at nearly 9Gs (nine times the force …
induced loss of consciousness, passing out while turning at nearly 9Gs (nine times the force …
Robust control barrier functions under high relative degree and input constraints for satellite trajectories
This paper presents methodologies for constructing Control Barrier Functions (CBFs) for
nonlinear, control-affine systems, in the presence of input constraints and bounded …
nonlinear, control-affine systems, in the presence of input constraints and bounded …
High relative degree control barrier functions under input constraints
This paper presents methodologies for ensuring forward invariance of sublevel sets of
constraint functions with high-relative-degree with respect to the system dynamics and in the …
constraint functions with high-relative-degree with respect to the system dynamics and in the …
Safe reinforcement learning using robust control barrier functions
Reinforcement Learning (RL) has been shown to be effective in many scenarios. However, it
typically requires the exploration of a sufficiently large number of state-action pairs, some of …
typically requires the exploration of a sufficiently large number of state-action pairs, some of …
Differentiable safe controller design through control barrier functions
Learning-based controllers, such as neural network (NN) controllers, can show high
empirical performance but lack formal safety guarantees. To address this issue, control …
empirical performance but lack formal safety guarantees. To address this issue, control …
How to train your neural control barrier function: Learning safety filters for complex input-constrained systems
Control barrier functions (CBFs) have become popular as a safety filter to guarantee the
safety of nonlinear dynamical systems for arbitrary inputs. However, it is difficult to construct …
safety of nonlinear dynamical systems for arbitrary inputs. However, it is difficult to construct …