Search Results for author:
Found 2 papers, 0 papers with code
Safe end-to-end imitation learning for model predictive control
We propose the use of Bayesian networks, which provide both a mean value and an uncertainty estimate as output, to enhance the safety of learned control policies under circumstances in which a test-time input differs significantly from the training set.
Imitation Learning for Agile Autonomous Driving
We present an end-to-end imitation learning system for agile, off-road autonomous driving using only low-cost on-board sensors.
Robotics
Cannot find the paper you are looking for? You can
Submit a new open access paper.
