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 …
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 …
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
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 …
Enforcing hard constraints with soft barriers: Safe reinforcement learning in unknown stochastic environments
It is quite challenging to ensure the safety of reinforcement learning (RL) agents in an
unknown and stochastic environment under hard constraints that require the system state …
unknown and stochastic environment under hard constraints that require the system state …
Reachability constrained reinforcement learning
Constrained reinforcement learning (CRL) has gained significant interest recently, since
safety constraints satisfaction is critical for real-world problems. However, existing CRL …
safety constraints satisfaction is critical for real-world problems. However, existing CRL …
Neural graph control barrier functions guided distributed collision-avoidance multi-agent control
We consider the problem of designing distributed collision-avoidance multi-agent control in
large-scale environments with potentially moving obstacles, where a large number of agents …
large-scale environments with potentially moving obstacles, where a large number of agents …
Neural lyapunov control of unknown nonlinear systems with stability guarantees
R Zhou, T Quartz, H De Sterck… - Advances in Neural …, 2022 - proceedings.neurips.cc
Learning for control of dynamical systems with formal guarantees remains a challenging
task. This paper proposes a learning framework to simultaneously stabilize an unknown …
task. This paper proposes a learning framework to simultaneously stabilize an unknown …
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 …
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 …