Max H. Cohen

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 model-based safety-critical...

Characterizing Smooth Safety Filters via the Implicit Function Theorem

Optimization-based safety filters, such as control barrier function (CBF) based quadratic programs (QPs), have demonstrated success in controlling autonomous systems to achieve complex goals....

Rectified Control Barrier Functions for High-Order Safety Constraints

This paper presents a novel approach for synthesizing control barrier functions (CBFs) from high relative degree safety constraints: Rectified CBFs (ReCBFs). We begin by discussing the limitations...

Constructive Safety-Critical Control: Synthesizing Control Barrier Functions for Partially Feedback Linearizable Systems

Certifying the safety of nonlinear systems, through the lens of set invariance and control barrier functions (CBFs), offers a powerful method for controller synthesis, provided a CBF can be...

Robust Control Barrier Functions for Nonlinear Control Systems with Uncertainty: A Duality-based Approach

This paper studies the design of controllers that guarantee stability and safety of nonlinear control affine systems with parametric uncertainty in both the drift and control vector fields. To...

High Order Robust Adaptive Control Barrier Functions and Exponentially Stabilizing Adaptive Control Lyapunov Functions

This paper studies the problem of utilizing data-driven adaptive control techniques to guarantee stability and safety of uncertain nonlinear systems with high relative degree. We first introduce...

Safe Exploration in Model-based Reinforcement Learning using Control Barrier Functions

This paper develops a model-based reinforcement learning (MBRL) framework for learning online the value function of an infinite-horizon optimal control problem while obeying safety constraints...

Vector Field Following for Quadrotors via Reduced Attitude Representations with Applications to Safety-Critical Control

Vector field tracking for quadrotors provides a systematic framework for specifying complex behaviors at the translational level and transferring them to the full vehicle dynamics. Objectives such...

Model-based reinforcement learning for approximate optimal control with temporal logic specifications

Modular Adaptive Safety-Critical Control

Control Barrier Functions for Flight-Critical Systems in Aerospace Applications

Input-to-State Safe Backstepping: Robust Safety-Critical Control with Unmatched Uncertainties

Uncertainty Quantification for Recursive Estimation in Adaptive Safety-Critical Control

Safety-Critical Controller Synthesis with Reduced-Order Models

Learning for Layered Safety-Critical Control with Predictive Control Barrier Functions

Approximate Optimal Control for Safety-Critical Systems with Control Barrier Functions

On the Properties of Optimal-Decay Control Barrier Functions

Robust Control Barrier Functions for Nonlinear Control Systems with Uncertainty: A Duality-based Approach