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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 …
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 …
characterized by high-dimensional nonlinear dynamics, which presents challenges for …
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 …
High-order control barrier functions
We approach the problem of stabilizing a dynamical system while optimizing a cost and
satisfying safety constraints and control limitations. For (nonlinear) affine control systems …
satisfying safety constraints and control limitations. For (nonlinear) affine control systems …
Barriernet: Differentiable control barrier functions for learning of safe robot control
Many safety-critical applications of neural networks, such as robotic control, require safety
guarantees. This article introduces a method for ensuring the safety of learned models for …
guarantees. This article introduces a method for ensuring the safety of learned models for …
Data-driven safety filters: Hamilton-jacobi reachability, control barrier functions, and predictive methods for uncertain systems
Today's control engineering problems exhibit an unprecedented complexity, with examples
including the reliable integration of renewable energy sources into power grids, safe …
including the reliable integration of renewable energy sources into power grids, safe …
Control barrier functions and input-to-state safety with application to automated vehicles
Balancing safety and performance is one of the predominant challenges in modern control
system design. Moreover, it is crucial to robustly ensure safety without inducing unnecessary …
system design. Moreover, it is crucial to robustly ensure safety without inducing unnecessary …
Learning safe multi-agent control with decentralized neural barrier certificates
We study the multi-agent safe control problem where agents should avoid collisions to static
obstacles and collisions with each other while reaching their goals. Our core idea is to learn …
obstacles and collisions with each other while reaching their goals. Our core idea is to learn …
Safe control under input limits with neural control barrier functions
We propose new methods to synthesize control barrier function (CBF) based safe controllers
that avoid input saturation, which can cause safety violations. In particular, our method is …
that avoid input saturation, which can cause safety violations. In particular, our method is …
Model-free safe reinforcement learning through neural barrier certificate
Safety is a critical concern when applying reinforcement learning (RL) to real-world control
tasks. However, existing safe RL works either only consider expected safety constraint …
tasks. However, existing safe RL works either only consider expected safety constraint …