首页> 外国专利> METHOD AND DEVICE FOR CALIBRATING PHYSICS ENGINE OF VIRTUAL WORLD SIMULATOR TO BE USED FOR LEARNING OF DEEP LEARNING-BASED DEVICE, AND A LEARNING METHOD AND LEARNING DEVICE FOR REAL STATE NETWORK USED THEREFOR

METHOD AND DEVICE FOR CALIBRATING PHYSICS ENGINE OF VIRTUAL WORLD SIMULATOR TO BE USED FOR LEARNING OF DEEP LEARNING-BASED DEVICE, AND A LEARNING METHOD AND LEARNING DEVICE FOR REAL STATE NETWORK USED THEREFOR

机译:用于学习基于深度学习的设备的虚拟世界仿真器的物理引擎的校准方法和设备,以及用于此方法的用于真实网络的学习方法和学习设备

摘要

A method for calibrating a physics engine of a virtual world simulator for learning of a deep learning-based device is provided. The method includes steps of a calibrating device (a) if virtual current frame information corresponding to a virtual current state in virtual environment is acquired, (i) transmitting the virtual current frame information to the deep learning-based device to output virtual action information, (ii) transmitting the virtual current frame information and the virtual action information to the physics engine to output virtual next frame information corresponding to the virtual current frame information and the virtual action information, and (iii) transmitting the virtual current frame information and the virtual action information to a real state network learned to output predicted next frame information in response to action in a real environment to output predicted real next frame information; and (b) optimizing the previous calibrated parameters to generate current calibrated parameters.
机译:提供了一种用于校准虚拟世界模拟器的物理引擎以学习基于深度学习的设备的方法。该方法包括校准设备的步骤:(a)如果获取了与虚拟环境中的虚拟当前状态相对应的虚拟当前帧信息,(i)将虚拟当前帧信息发送到基于深度学习的设备以输出虚拟动作信息; (ii)向物理引擎发送虚拟当前帧信息和虚拟动作信息,以输出与虚拟当前帧信息和虚拟动作信息相对应的虚拟下一帧信息,以及(iii)发送虚拟当前帧信息和虚拟动作信息。向真实状态网络的动作信息,其学会了响应于真实环境中的动作而输出预测的下一帧信息,以输出预测的下一帧信息; (b)优化先前的校准参数以生成当前的校准参数。

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