Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods for robotics and control
Learning-enabled control systems have demonstrated impressive empirical performance on
challenging control problems in robotics, but this performance comes at the cost of reduced …
challenging control problems in robotics, but this performance comes at the cost of reduced …
Learning safe control for multi-robot systems: Methods, verification, and open challenges
In this survey, we review the recent advances in control design methods for robotic multi-
agent systems (MAS), focusing on learning-based methods with safety considerations. We …
agent systems (MAS), focusing on learning-based methods with safety considerations. We …
Automated verification and synthesis of stochastic hybrid systems: A survey
Stochastic hybrid systems have received significant attentions as a relevant modeling
framework describing many systems, from engineering to the life sciences: they enable the …
framework describing many systems, from engineering to the life sciences: they enable the …
Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods
Learning-enabled control systems have demonstrated impressive empirical performance on
challenging control problems in robotics, but this performance comes at the cost of reduced …
challenging control problems in robotics, but this performance comes at the cost of reduced …
Exact verification of relu neural control barrier functions
Abstract Control Barrier Functions (CBFs) are a popular approach for safe control of
nonlinear systems. In CBF-based control, the desired safety properties of the system are …
nonlinear systems. In CBF-based control, the desired safety properties of the system are …
Safety certification for stochastic systems via neural barrier functions
FB Mathiesen, SC Calvert… - IEEE Control Systems …, 2022 - ieeexplore.ieee.org
Providing non-trivial certificates of safety for non-linear stochastic systems is an important
open problem. One promising solution to address this problem is the use of barrier functions …
open problem. One promising solution to address this problem is the use of barrier functions …
Compositional policy learning in stochastic control systems with formal guarantees
Reinforcement learning has shown promising results in learning neural network policies for
complicated control tasks. However, the lack of formal guarantees about the behavior of …
complicated control tasks. However, the lack of formal guarantees about the behavior of …
Physics-informed neural network Lyapunov functions: PDE characterization, learning, and verification
We provide a systematic investigation of using physics-informed neural networks to compute
Lyapunov functions. We encode Lyapunov conditions as a partial differential equation (PDE) …
Lyapunov functions. We encode Lyapunov conditions as a partial differential equation (PDE) …
Automated and formal synthesis of neural barrier certificates for dynamical models
We introduce an automated, formal, counterexample-based approach to synthesise Barrier
Certificates (BC) for the safety verification of continuous and hybrid dynamical models. The …
Certificates (BC) for the safety verification of continuous and hybrid dynamical models. The …
Effects of chemical pollution on the behaviour of cichlid fish
HF Olivares-Rubio, E Arce - Environmental Biology of Fishes, 2023 - Springer
Pollution is one of the most relevant issues for the conservation of freshwater environments.
Fishes are the main group of organisms studied in aquatic toxicology, and their behaviours …
Fishes are the main group of organisms studied in aquatic toxicology, and their behaviours …