Transporter Network for Determining Robot Actions
卷宗概要
发明人
Andy Zeng
IPC 分类
CPC 分类
A transporter network for determining robot actions based on sensor feedback can afford robots with efficient autonomous movement. The transporter network may exploit spatial symmetries and may not need assumptions of objectness to provide accurate instructions on object manipulation. The machine-learned model of the transporter network may also allow for learning various tasks with less training examples than other machine-learned models. The machine-learned model of the transporter network may intake observation data as input and may output actions in response to the processed observation data.
原文（中文）
A transporter network for determining robot actions based on sensor feedback can afford robots with efficient autonomous movement. The transporter network may exploit spatial symmetries and may not need assumptions of objectness to provide accurate instructions on object manipulation. The machine-learned model of the transporter network may also allow for learning various tasks with less training examples than other machine-learned models. The machine-learned model of the transporter network may intake observation data as input and may output actions in response to the processed observation data.