A Platform for Robotics Research Based on the Remote-Brained Robot Approach

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Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates (2016, background): “Accelerating robotic learning by pooling experience from multiple robots has long been recognized as a promising direction in the domain of cloud robotics, where it is typically referred to as collective robotic learning [31], [32], [33], [34].”
Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection (2016, background): “More broadly, the ability of robotic systems to learn more quickly by pooling their collective experience has been proposed in a number of prior works, and has been referred to as collective robot learning and an instance of cloud robotics (Inaba et al., 2000; Kehoe et al., 2013, 2015; Kuffner, 2010”
Collective robot reinforcement learning with distributed asynchronous guided policy search (2016, background): “The ability of robotic systems to learn more quickly and effectively by pooling their collective experience has long been recognized in the domain of cloud robotics, where it is typically referred to as collective robotic learning [11, 12, 13, 14].”
Humanoid motion generation system on HRP2-JSK for daily life environment (2005, methodology): “This system is built on the software environment developed in the remote-brained robotics research [1].”