From Reinforcement Learning to Robot Learning: Leveraging Prior Data and Shared Evaluation

NSH 4305

Abstract: Unlike most machine learning applications, robotics involves physical constraints that make off-the-shelf learning challenging. Difficulties in large-scale data collection and training present a major roadblock to applying today’s data-intensive algorithms. Robot learning has an additional roadblock in evaluation: every physical space is different, making results across labs inconsistent. Two common assumptions of the robot [...]