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 …

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 …

Learning-enabled control systems have demonstrated impressive empirical performance on
challenging control problems in robotics, but this performance comes at the cost of reduced …

Learning-enabled control systems have demonstrated impressive empirical performance on
challenging control problems in robotics, but this performance comes at the cost of reduced …

This paper presents methodologies for constructing Control Barrier Functions (CBFs) for
nonlinear, control-affine systems, in the presence of input constraints and bounded …

Safety is one of the fundamental problems in robotics. Recently, a quadratic program based
control barrier function (CBF) method has emerged as a way to enforce safety-critical …

Abstract We propose a Safe Pontryagin Differentiable Programming (Safe PDP)
methodology, which establishes a theoretical and algorithmic framework to solve a broad …

This paper addresses learning safe output feedback control laws from partial observations of
expert demonstrations. We assume that a model of the system dynamics and a state …

There have been tremendous developments in theories and technologies in control for
smart systems. In this paper we review applications to various systems that are crucial for the …

Model-based reinforcement learning has been widely studied for controller synthesis in
cyber-physical systems (CPSs). In particular, for safety-critical CPSs, it is important to …