Safe active dynamics learning and control: A sequential exploration–exploitation framework

T Lew, A Sharma, J Harrison, A Bylard… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Safe deployment of autonomous robots in diverse scenarios requires agents that are
capable of efficiently adapting to new environments while satisfying constraints. In this …

Data-driven chance constrained control using kernel distribution embeddings

A Thorpe, T Lew, M Oishi… - Learning for Dynamics …, 2022 - proceedings.mlr.press
We present a data-driven algorithm for efficiently computing stochastic control policies for
general joint chance constrained optimal control problems. Our approach leverages the …

Probabilistic safe online learning with control barrier functions

F Castaneda, JJ Choi, W Jung, B Zhang… - arxiv preprint arxiv …, 2022 - arxiv.org
Learning-based control schemes have recently shown great efficacy performing complex
tasks. However, in order to deploy them in real systems, it is of vital importance to guarantee …

Optimized control invariance conditions for uncertain input-constrained nonlinear control systems

L Brunke, S Zhou, M Che… - IEEE Control Systems …, 2023 - ieeexplore.ieee.org
Providing safety guarantees for learning-based controllers is important for real-world
applications. One approach to realizing safety for arbitrary control policies is safety filtering. If …

Safe Control of Robotic Systems under Uncertainty: Reconciling Model-based and Data-driven Methods

F Castaneda Garcia-Rozas - 2023 - escholarship.org
Safety is a primary concern for deploying autonomous robots in the real world. Model-based
control theoretic tools provide formal safety guarantees when a mathematical model of the …

[BOOK][B] Safe Control of Robotic Systems Under Uncertainty: Reconciling Model-Based and Data-Driven Methods

FC Garcia-Rozas - 2023 - search.proquest.com
Safety is a primary concern for deploying autonomous robots in the real world. Model-based
control theoretic tools provide formal safety guarantees when a mathematical model of the …

[BOOK][B] Uncertainty-Aware Control, Planning, and Learning for Reliable Robotic Autonomy

TJ Lew - 2023 - search.proquest.com
As autonomous systems take on increasingly challenging tasks in safety-critical settings
such as autonomous driving and aerospace, their ability to explicitly account for uncertainty …