So You Think You Can Scale Up Autonomous Robot Data Collection?

arxiv.org · 13,214 words · saved by 1 readers

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So You Think You Can Scale Up Autonomous Robot Data Collection? Abstract A long-standing goal in robot learning is to develop methods for robots to acquire new skills autonomously. While reinforcement learning (RL) comes with the promise of enabling autonomous data collection, it remains challenging to scale in the real-world partly due to the significant effort required for environment design and instrumentation, including the need for designing reset functions or accurate success detectors. On the other hand, imitation learning (IL) methods require little to no environment design effort, but

So You Think You Can Scale Up Autonomous Robot Data Collection?

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