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CONTROLLING A ROBOT BASED ON FREE-FORM NATURAL LANGUAGE INPUT
CONTROLLING A ROBOT BASED ON FREE-FORM NATURAL LANGUAGE INPUT
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机译:基于自由形式自然语言输入的机器人控制
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摘要
Implementations relate to using deep reinforcement learning to train a model that can be utilized, at each of a plurality of time steps, to determine a corresponding robotic action for completing a robotic task. Implementations additionally or alternatively relate to utilization of such a model in controlling a robot. The robotic action determined at a given time step utilizing such a model can be based on: current sensor data associated with the robot for the given time step, and free-form natural language input provided by a user. The free-form natural language input can direct the robot to accomplish a particular task, optionally with reference to one or more intermediary steps for accomplishing the particular task. For example, the free-form natural language input can direct the robot to navigate to a particular landmark, with reference to one or more intermediary landmarks to be encountered in navigating to the particular landmark.
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