Autonomous drifting using simulation-aided reinforcement learning

ICRA, pp. 5442-5448, 2016.

Cited by: 31|Views4
EI

Abstract:

We introduce a framework that combines simple and complex continuous state-action simulators with a real-world robot to efficiently find good control policies, while minimizing the number of samples needed from the physical robot. The framework combines the strengths of various simulation levels by first finding optimal policies in a simp...More

Code:

Data:

Get fulltext within 24h
Bibtex
Your rating :
0

 

Tags
Comments