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 …
[HTML][HTML] NNV: the neural network verification tool for deep neural networks and learning-enabled cyber-physical systems
This paper presents the Neural Network Verification (NNV) software tool, a set-based
verification framework for deep neural networks (DNNs) and learning-enabled cyber …
verification framework for deep neural networks (DNNs) and learning-enabled cyber …
Risk-averse autonomous systems: A brief history and recent developments from the perspective of optimal control
Y Wang, MP Chapman - Artificial Intelligence, 2022 - Elsevier
We present an historical overview about the connections between the analysis of risk and
the control of autonomous systems. We offer two main contributions. Our first contribution is …
the control of autonomous systems. We offer two main contributions. Our first contribution is …
Testing deep neural networks
Deep neural networks (DNNs) have a wide range of applications, and software employing
them must be thoroughly tested, especially in safety-critical domains. However, traditional …
them must be thoroughly tested, especially in safety-critical domains. However, traditional …
Reachnn: Reachability analysis of neural-network controlled systems
Applying neural networks as controllers in dynamical systems has shown great promises.
However, it is critical yet challenging to verify the safety of such control systems with neural …
However, it is critical yet challenging to verify the safety of such control systems with neural …
[HTML][HTML] Verification of deep convolutional neural networks using imagestars
Abstract Convolutional Neural Networks (CNN) have redefined state-of-the-art in many real-
world applications, such as facial recognition, image classification, human pose estimation …
world applications, such as facial recognition, image classification, human pose estimation …
Stability analysis using quadratic constraints for systems with neural network controllers
A method is presented to analyze the stability of feedback systems with neural network
controllers. Two stability theorems are given to prove asymptotic stability and to compute an …
controllers. Two stability theorems are given to prove asymptotic stability and to compute an …
Reachable set estimation for neural network control systems: A simulation-guided approach
The vulnerability of artificial intelligence (AI) and machine learning (ML) against adversarial
disturbances and attacks significantly restricts their applicability in safety-critical systems …
disturbances and attacks significantly restricts their applicability in safety-critical systems …
Safety verification of cyber-physical systems with reinforcement learning control
This paper proposes a new forward reachability analysis approach to verify safety of cyber-
physical systems (CPS) with reinforcement learning controllers. The foundation of our …
physical systems (CPS) with reinforcement learning controllers. The foundation of our …
Structural test coverage criteria for deep neural networks
Deep neural networks (DNNs) have a wide range of applications, and software employing
them must be thoroughly tested, especially in safety-critical domains. However, traditional …
them must be thoroughly tested, especially in safety-critical domains. However, traditional …