STAGE-WISE LEARNING OF REACHING USING LITTLE PRIOR KNOWLEDGE

Stage-Wise Learning of Reaching Using Little Prior Knowledge

In some manipulation robotics environments, because of the difficulty of precisely modeling dynamics and computing features which describe well the variety of scene appearances, hand-programming a robot behavior is often intractable.Deep reinforcement learning methods partially alleviate this problem in that they can dispense with hand-crafted feat

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Concentric ring optical traps for orbital rotation of particles

Optical vortices (OVs), as eigenmodes of optical orbital angular momentum, have been widely used in particle micro-manipulation.Recently, perfect optical vortices (POVs), a subclass of OVs, are gaining increasing interest and becoming an indispensable tool in optical trapping due to their unique property of topological charge-independent vortex rad

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Activity Monitoring with a Wrist-Worn, Accelerometer-Based Device

This study condenses huge amount of raw data measured from a MEMS accelerometer-based, wrist-worn device on different levels of physical activities (PAs) for subjects wearing the device 24 h a day continuously.In this study, we have employed the device to build up assessment models for quantifying activities, to develop an algorithm for sleep durat

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