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09/14/2023
A Bayesian approach to breaking things: efficiently predicting and repairing failure modes via sampling
Before autonomous systems can be deployed in safety-critical application...
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02/23/2023
Shield Model Predictive Path Integral: A Computationally Efficient Robust MPC Approach Using Control Barrier Functions
Model Predictive Path Integral (MPPI) control is a type of sampling-base...
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01/31/2023
Chance-Constrained Trajectory Optimization for High-DOF Robots in Uncertain Environments
Many practical applications of robotics require systems that can operate...
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09/25/2022
Enforcing safety for vision-based controllers via Control Barrier Functions and Neural Radiance Fields
To navigate complex environments, robots must increasingly use high-dime...
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04/22/2022
Certifiable Robot Design Optimization using Differentiable Programming
There is a growing need for computational tools to automatically design ...
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03/03/2022
Robust Counterexample-guided Optimization for Planning from Differentiable Temporal Logic
Signal temporal logic (STL) provides a powerful, flexible framework for ...
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02/23/2022
Safe Control with Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction methods
Learning-enabled control systems have demonstrated impressive empirical ...
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01/04/2022
Learning Safe, Generalizable Perception-based Hybrid Control with Certificates
Many robotic tasks require high-dimensional sensors such as cameras and ...
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09/14/2021
Safe Nonlinear Control Using Robust Neural Lyapunov-Barrier Functions
Safety and stability are common requirements for robotic control systems...
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03/17/2020
Provably Safe Trajectory Optimization in the Presence of Uncertain Convex Obstacles
Real-world environments are inherently uncertain, and to operate safely ...
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03/17/2020