Estimating High Probability Reachable Sets using Gaussian Processes-Reference-Cited by-同舟云学术

Estimating High Probability Reachable Sets using Gaussian Processes

Published:2021-12-14 Issue: Volume: Page:
ISSN:
Container-title:2021 60th IEEE Conference on Decision and Control (CDC)
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Author:

Cao Michael E.,Bloch Matthieu,Coogan Samuel

Funder

National Science Foundation

Air Force Office of Scientific Research

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9682670/9682776/09682962.pdf?arnumber=9682962

Reference18 articles.

1. Gaussian Processes for Learning and Control: A Tutorial with Examples

2. Distributed environmental modeling and adaptive sampling for multi-robot sensor coverage;luo;Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems AAMAS ’19 (Richland SC),2019

3. Multi-Robot Coordination for Estimation and Coverage of Unknown Spatial Fields

4. Uniform error bounds for Gaussian Process regression with application to safe control;lederer;Advances in neural information processing systems,2019

5. Probabilistic safety constraints for learned high relative degree system dynamics;khojasteh;Proceedings of the 2nd Conference on Learning for Dynamics and Control vol 120 of Proceedings of Machine Learning Research,2020

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3. Safe Learning-based Predictive Control from Efficient Reachability;2023 American Control Conference (ACC);2023-05-31

4. Efficient Learning of Hyperrectangular Invariant Sets Using Gaussian Processes;IEEE Open Journal of Control Systems;2022