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The safety filter: A unified view of safety-critical control in autonomous systems
Recent years have seen significant progress in the realm of robot autonomy, accompanied
by the expanding reach of robotic technologies. However, the emergence of new …
by the expanding reach of robotic technologies. However, the emergence of new …
Safety-critical control for autonomous systems: Control barrier functions via reduced-order models
Modern autonomous systems, such as flying, legged, and wheeled robots, are generally
characterized by high-dimensional nonlinear dynamics, which presents challenges for …
characterized by high-dimensional nonlinear dynamics, which presents challenges for …
Data-driven safety filters: Hamilton-jacobi reachability, control barrier functions, and predictive methods for uncertain systems
Today's control engineering problems exhibit an unprecedented complexity, with examples
including the reliable integration of renewable energy sources into power grids, safe …
including the reliable integration of renewable energy sources into power grids, safe …
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 …
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 …
Convex synthesis of control barrier functions under input constraints
This letter presents a systematic method based on the sum of square (SOS) optimization to
synthesize control barrier functions (CBFs) for nonlinear polynomial systems subject to input …
synthesize control barrier functions (CBFs) for nonlinear polynomial systems subject to input …
Verification and synthesis of robust control barrier functions: Multilevel polynomial optimization and semidefinite relaxation
We study the problem of verification and synthesis of robust control barrier functions (CBF)
for control-affine polynomial systems with bounded additive uncertainty and convex …
for control-affine polynomial systems with bounded additive uncertainty and convex …
Constructing control lyapunov-value functions using hamilton-jacobi reachability analysis
In this letter, we seek to build connections between control Lyapunov functions (CLFs) and
Hamilton-Jacobi (HJ) reachability analysis. CLFs have been used extensively in the control …
Hamilton-Jacobi (HJ) reachability analysis. CLFs have been used extensively in the control …
Learning safe control for multi-robot systems: Methods, verification, and open challenges
In this survey, we review the recent advances in control design methods for robotic multi-
agent systems (MAS), focusing on learning-based methods with safety considerations. We …
agent systems (MAS), focusing on learning-based methods with safety considerations. We …
A forward reachability perspective on robust control invariance and discount factors in reachability analysis
Control invariant sets are crucial for various methods that aim to design safe control policies
for systems whose state constraints must be satisfied over an indefinite time horizon. In this …
for systems whose state constraints must be satisfied over an indefinite time horizon. In this …