公开(公告)号：US20160096270A1

公开(公告)日：2016-04-07

申请号：US14542391

申请日：2014-11-14

Applicant: Brain Corporation

Inventor： Borja Ibarz Gabardos ,  Andrew Smith ,  Peter O'Connor

IPC: B25J9/16

CPC classification number: B25J9/163 ,  B25J9/1607 ,  B25J9/1666 ,  B25J9/1697 ,  G05D1/0088 ,  G05D1/0246 ,  G05D2201/02 ,  G06N3/00 ,  G06N3/008 ,  G06N3/049 ,  Y10S901/01 ,  Y10S901/03 ,  Y10S901/09 ,  Y10S901/47

Abstract: A robotic device may be operated by a learning controller comprising a feature learning configured to determine control signal based on sensory input. An input may be analyzed in order to determine occurrence of one or more features. Features in the input may be associated with the control signal during online supervised training. During training, learning process may be adapted based on training input and the predicted output. A combination of the predicted and the target output may be provided to a robotic device to execute a task. Feature determination may comprise online adaptation of input, sparse encoding transformations. Computations related to learning process adaptation and feature detection may be performed on board by the robotic device in real time thereby enabling autonomous navigation by trained robots.

Abstract translation: 机器人设备可以由包括被配置为基于感觉输入来确定控制信号的特征学习的学习控制器操作。 可以分析输入以确定一个或多个特征的发生。 输入中的特征可能与在线监督训练期间的控制信号相关联。 在训练中，学习过程可以根据训练输入和预测输出进行调整。 可以将预测和目标输出的组合提供给机器人装置以执行任务。 特征确定可以包括输入，稀疏编码变换的在线适配。 与学习过程适应和特征检测相关的计算可以由机器人设备实时执行，从而使训练有素的机器人能够进行自主导航。