Experiment design with gaussian process regression with applications to chance-constrained control
Learning for control in repeated tasks allows for well-designed experiments to gather the
most useful data. We consider the setting in which we use a data-driven controller that does …
most useful data. We consider the setting in which we use a data-driven controller that does …
Ensemble gaussian processes for adaptive autonomous driving on multi-friction surfaces
Driving under varying road conditions is challenging, especially for autonomous vehicles
that must adapt in real-time to changes in the environment, eg, rain, snow, etc. It is difficult to …
that must adapt in real-time to changes in the environment, eg, rain, snow, etc. It is difficult to …
Distributed experiment design and control for multi-agent systems with gaussian processes
This paper focuses on distributed learning-based control of decentralized multi-agent
systems where the agents' dynamics are modeled by Gaussian Processes (GPs). Two …
systems where the agents' dynamics are modeled by Gaussian Processes (GPs). Two …
[PDF][PDF] Experiment Design with Gaussian Process Regression with Applications to Risk-Aware Control
S Anderson, K Byl, JP Hespanha - ece.ucsb.edu
Learning for control in repeated tasks allows for well-designed experiments to gather the
most useful data. We consider the setting in which we use a data-driven controller that does …
most useful data. We consider the setting in which we use a data-driven controller that does …