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METHOD AND SYSTEM FOR ROBOT ACTION IMITATION LEARNING IN THREE-DIMENSIONAL SPACE

机译:三维空间机器人动作模仿学习的方法和系统

摘要

The present invention provides a method for robot action imitation learning in a three-dimensional space and a system thereof, relates to the technical fields of artificial intelligence and robots. A method based on a series-parallel multi-layer backpropagation (BP) neural network is designed for robot action imitation learning in a three-dimensional space, which applies an imitation learning mechanism to a robot learning system, under the framework of the imitation learning mechanism, to train and learn by transmitting demonstrative information generated from a mechanical arm to the series-parallel multi-layer BP neural network representing a motion strategy. The correspondence between a state characteristic matrix set of the motion and an action characteristic matrix set of the motion is learned, to reproduce the demonstrative action, and generalize the actions and behaviors, so that when facing different tasks, the method does not need to carry out action planning separately, thereby achieving high intelligence.
机译:本发明提供了一种用于在三维空间中的机器人动作模拟学习的方法,以及其系统,涉及人工智能和机器人的技术领域。基于串联的多层反向作格(BP)神经网络的方法是为三维空间中的机器人动作模拟学习设计,这将模仿学习机制应用于仿制学习的框架下的机器人学习系统通过将从机械臂产生的说明性信息传输到表示运动策略的串联的多层BP神经网络来训练和学习。学习的运动和动作特征矩阵集之间的状态特征矩阵集之间的对应关系,以再现演示操作,并概括了动作和行为,使得当面对不同的任务时,该方法不需要携带单独行动规划,从而实现高智智能。

著录项

  • 公开/公告号US2021299860A1

    专利类型

  • 公开/公告日2021-09-30

    原文格式PDF

  • 申请/专利权人 HEFEI UNIVERSITY OF TECHNOLOGY;

    申请/专利号US202017068864

  • 发明设计人 MINGLUN REN;YUANYUAN MA;

    申请日2020-10-13

  • 分类号B25J9/16;B25J13/08;

  • 国家 US

  • 入库时间 2022-08-24 21:22:44

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