Stochastic Grounded Action Transformation for Robot Learning in Simulation
Siddharth Desai,Haresh Karnan,Josiah P. Hanna,Garrett Warnell,and Peter Stone,Siddharth Desai,Haresh Karnan,Josiah P. Hanna,Garrett Warnell,and Peter Stone
Robot control policies learned in simulation do not often transfer well to the real world. Many existing solutions to this sim-to-real problem, such as the Grounded Action Transformation (GAT) algorithm, seek to correct for- or ground-these differences by matching the simulator to the real world. However, the efficacy of these approaches is limited if they do not explicitly account for stochastici...
