Abstract: Asynchronous robotic control utilizing a trained critic network. During performance of a robotic task based on a sequence of robotic actions determined utilizing the critic network, a corresponding next robotic action of the sequence is determined while a corresponding previous robotic action of the sequence is still being implemented. Optionally, the next robotic action can be fully determined and/or can begin to be implemented before implementation of the previous robotic action is completed. In determining the next robotic action, most recently selected robotic action data is processed using the critic network, where such data conveys information about the previous robotic action that is still being implemented. Some implementations additionally or alternatively relate to determining when to implement a robotic action that is determined in an asynchronous manner.

Abstract: Using large-scale reinforcement learning to train a policy model that can be utilized by a robot in performing a robotic task in which the robot interacts with one or more environmental objects. In various implementations, off-policy deep reinforcement learning is used to train the policy model, and the off-policy deep reinforcement learning is based on self-supervised data collection. The policy model can be a neural network model. Implementations of the reinforcement learning utilized in training the neural network model utilize a continuous-action variant of Q-learning. Through techniques disclosed herein, implementations can learn policies that generalize effectively to previously unseen objects, previously unseen environments, etc.

Abstract: Various embodiments may provide an optical system for determining a refractive index of a sample. The optical system may include a laser source configured to emit a laser beam, and a non-linear crystal configured to generate, based on the laser beam, an infrared light beam which passes through the sample, and a visible signal light beam. The optical system may further include a first mirror configured to reflect the visible signal light beam, a second mirror configured to reflect the infrared light beam so that the reflected infrared light beam interacts with the reflected visible signal light beam in the non-linear crystal, and a photodetector configured to determine a property of the reflected visible signal light beam which has interacted with the reflected infrared light beam for determining the refractive index of the sample.

Abstract: Various embodiments may provide an optical system for determining a refractive index of a sample. The optical system may include a laser source configured to emit a laser beam, and a non-linear crystal configured to generate, based on the laser beam, an infrared light beam which passes through the sample, and a visible signal light beam. The optical system may further include a first mirror configured to reflect the visible signal light beam, a second mirror configured to reflect the infrared light beam so that the reflected infrared light beam interacts with the reflected visible signal light beam in the non-linear crystal, and a photodetector configured to determine a property of the reflected visible signal light beam which has interacted with the reflected infrared light beam for determining the refractive index of the sample.