87 citations · 279 across the 16 of their papers we have counts for
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cs.RO2018★ 17 cited
GPU-Accelerated Robotic Simulation for Distributed Reinforcement Learning
Jacky Liang, Viktor Makoviychuk, Ankur Handa +3
Most Deep Reinforcement Learning (Deep RL) algorithms require a prohibitively large number of training samples for learning complex tasks. Many recent works on speeding up Deep RL…
cs.RO2018
Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience
Yevgen Chebotar, Ankur Handa, Viktor Makoviychuk +4
We consider the problem of transferring policies to the real world by training on a distribution of simulated scenarios. Rather than manually tuning the randomization of simulation…