Randomizing camera position during simulated robot-arm training improves robustness to viewpoint changes by about 25 percent average accuracy over fixed-camera training, at the same training budget.
Foundations and Trends in Machine Learning 11(3-4), 219–354 (2018)
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Learning more with the same effort: how randomization improves the robustness of a robotic deep reinforcement learning agent
Randomizing camera position during simulated robot-arm training improves robustness to viewpoint changes by about 25 percent average accuracy over fixed-camera training, at the same training budget.