Safe nonlinear control using robust neural lyapunov-barrier functions
Safety and stability are common requirements for robotic control systems; however,
designing safe, stable controllers remains difficult for nonlinear and uncertain models. We …
designing safe, stable controllers remains difficult for nonlinear and uncertain models. We …
A general safety framework for learning-based control in uncertain robotic systems
The proven efficacy of learning-based control schemes strongly motivates their application
to robotic systems operating in the physical world. However, guaranteeing correct operation …
to robotic systems operating in the physical world. However, guaranteeing correct operation …
Robust control barrier–value functions for safety-critical control
This paper works towards unifying two popular approaches in the safety control community:
Hamilton-Jacobi (HJ) reachability and Control Barrier Functions (CBFs). HJ Reachability has …
Hamilton-Jacobi (HJ) reachability and Control Barrier Functions (CBFs). HJ Reachability has …
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 …
LQR-trees: Feedback motion planning via sums-of-squares verification
Advances in the direct computation of Lyapunov functions using convex optimization make it
possible to efficiently evaluate regions of attraction for smooth non-linear systems. Here we …
possible to efficiently evaluate regions of attraction for smooth non-linear systems. Here we …
Probabilistic reachability and safety for controlled discrete time stochastic hybrid systems
In this work, probabilistic reachability over a finite horizon is investigated for a class of
discrete time stochastic hybrid systems with control inputs. A suitable embedding of the …
discrete time stochastic hybrid systems with control inputs. A suitable embedding of the …
Decentralized receding horizon control for large scale dynamically decoupled systems
We present a detailed study on the design of decentralized receding horizon control (RHC)
schemes for decoupled systems. We formulate an optimal control problem for a set of …
schemes for decoupled systems. We formulate an optimal control problem for a set of …
Bridging hamilton-jacobi safety analysis and reinforcement learning
Safety analysis is a necessary component in the design and deployment of autonomous
robotic systems. Techniques from robust optimal control theory, such as Hamilton-Jacobi …
robotic systems. Techniques from robust optimal control theory, such as Hamilton-Jacobi …
The flexible, extensible and efficient toolbox of level set methods
IM Mitchell - Journal of Scientific Computing, 2008 - Springer
Level set methods are a popular and powerful class of numerical algorithms for dynamic
implicit surfaces and solution of Hamilton-Jacobi PDEs. While the advanced level set …
implicit surfaces and solution of Hamilton-Jacobi PDEs. While the advanced level set …
A level set method for determining critical curvatures for drainage and imbibition
An accurate description of the mechanics of pore level displacement of immiscible fluids
could significantly improve the predictions from pore network models of capillary pressure …
could significantly improve the predictions from pore network models of capillary pressure …