The safety filter: A unified view of safety-critical control in autonomous systems

KC Hsu, H Hu, JF Fisac - Annual Review of Control, Robotics …, 2023 - annualreviews.org
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 …

Safety-critical control for autonomous systems: Control barrier functions via reduced-order models

MH Cohen, TG Molnar, AD Ames - Annual Reviews in Control, 2024 - Elsevier
Modern autonomous systems, such as flying, legged, and wheeled robots, are generally
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

KP Wabersich, AJ Taylor, JJ Choi… - IEEE Control …, 2023 - ieeexplore.ieee.org
Today's control engineering problems exhibit an unprecedented complexity, with examples
including the reliable integration of renewable energy sources into power grids, safe …

Safe control under input limits with neural control barrier functions

S Liu, C Liu, J Dolan - Conference on Robot Learning, 2023 - proceedings.mlr.press
We propose new methods to synthesize control barrier function (CBF) based safe controllers
that avoid input saturation, which can cause safety violations. In particular, our method is …

How to train your neural control barrier function: Learning safety filters for complex input-constrained systems

O So, Z Serlin, M Mann, J Gonzales… - … on Robotics and …, 2024 - ieeexplore.ieee.org
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 …

Advances in the theory of control barrier functions: Addressing practical challenges in safe control synthesis for autonomous and robotic systems

K Garg, J Usevitch, J Breeden, M Black… - Annual Reviews in …, 2024 - Elsevier
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 …

Marc: Multipolicy and risk-aware contingency planning for autonomous driving

T Li, L Zhang, S Liu, S Shen - IEEE Robotics and Automation …, 2023 - ieeexplore.ieee.org
Generating safe and non-conservative behaviors in dense, dynamic environments remains
challenging for automated vehicles due to the stochastic nature of traffic participants' …

Runtime assurance for safety-critical systems: An introduction to safety filtering approaches for complex control systems

KL Hobbs, ML Mote, MCL Abate… - IEEE Control …, 2023 - ieeexplore.ieee.org
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 …

Onboard safety guarantees for racing drones: High-speed geofencing with control barrier functions

A Singletary, A Swann, Y Chen… - IEEE Robotics and …, 2022 - ieeexplore.ieee.org
This letter details the theory and implementation behind practically ensuring safety of
remotely piloted racing drones. We demonstrate robust and practical safety guarantees on a …

Gcbf+: A neural graph control barrier function framework for distributed safe multi-agent control

S Zhang, O So, K Garg, C Fan - IEEE Transactions on Robotics, 2025 - ieeexplore.ieee.org
Distributed, scalable, and safe control of large-scale multi-agent systems is a challenging
problem. In this paper, we design a distributed framework for safe multi-agent control in …