The backup control barrier function (CBF) was recently proposed as a tractable formulation
that guarantees the feasibility of the CBF quadratic programming (QP) via an implicitly …

We introduce sparse polynomial zonotopes, a new set representation for formal verification
of hybrid systems. Sparse polynomial zonotopes can represent nonconvex sets and are …

Ensuring the safety of autonomous vehicles (AV s) in uncertain traffic scenarios is a major
challenge. In this paper, we address the problem of computing the risk that AV s violate a …

In this paper, we consider autonomous driving of miniature race cars. The viability kernel is
used to efficiently generate finite look-ahead trajectories that maximize progress while …

This paper presents two new control approaches for guaranteed safety (remaining in a safe
set) subject to actuator constraints (the control is in a convex polytope). The control signals …

Reinforcement learning (RL) agents are vulnerable to adversarial disturbances, which can
deteriorate task performance or break down safety specifications. Existing methods either …

Designing safety-critical control for robotic manipulators is challenging, especially in a
cluttered environment. This article proposes an online control barrier function (CBF) …

This article introduces an alternative characterization, together with indirect computation and
implicit representation, of the maximal positively invariant set for the nonlinear dynamics and …

Safe reinforcement learning (RL) aims to satisfy safety constraints during training. However,
guaranteeing safety during training remained a challenging problem. This paper presents a …

We present a flexible data-driven method for dynamical system analysis that does not
require explicit model discovery. The method is rooted in well-established techniques for …