Validate on Sim, Detect on Real - Model Selection for Domain Randomization
Gal Leibovich,Guy Jacob,Shadi Endrawis,Gal Novik,Aviv Tamar,Gal Leibovich,Guy Jacob,Shadi Endrawis,Gal Novik,Aviv Tamar
A practical approach to learning robot skills, often termed sim2real, is to train control policies in simulation and then deploy them on a real robot. Popular sim2real techniques build on domain randomization (DR) - training the policy on diverse randomly generated domains for better generalization to the real world. Due to the large number of hyper-parameters in both the policy learning and DR al...
