Sim To Real Transfer Through Domain Randomization And Robust Policy Training

via “sim-to-real transfer through domain randomization and robust policy training”

* ⭐ 02/2022: [BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning](https://proceedings.mlr.press/v164/jang22a.html)

Unique: Combines domain randomization in simulation with targeted fine-tuning on real-world data, using robust training objectives that prevent catastrophic forgetting of simulation-learned features while adapting to real-world dynamics. The approach treats simulation and real-world data as complementary rather than competing sources.