会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 4. 发明授权
    • Robot apparatus, and behavior controlling method for robot apparatus
    • 机器人装置和机器人装置的行为控制方法
    • US07103447B2
    • 2006-09-05
    • US10651577
    • 2003-08-29
    • Ugo Di ProfioMasahiro FujitaTsuyoshi TakagiYukiko YoshiikeHideki Shimomura
    • Ugo Di ProfioMasahiro FujitaTsuyoshi TakagiYukiko YoshiikeHideki Shimomura
    • G06F19/00
    • G06N3/008
    • A robot (1) is provided which includes a situated behaviors layer (SBL) (58). This SBL (58) is formed in the form of a tree structure in which a plurality of schemata (behavior modules) is connected hierarchically in such a matter that the schemata are highly independent of each other for each of them to behave uniquely. A patent schema can define a pattern in which child schemata are connected, such as an OR type pattern in which the child schemata are caused to behave uniquely, AND type pattern in which the plurality of child schemata are caused to behave simultaneously or a SEQUENCE type pattern indicating a sequence in which the plurality of child schemata should behave, thereby permitting to select a behavior pattern of the robot (1). Also, a new child schema can additionally be included in the SBL (58) without having to rewrite the schemata connection in the tree structure, whereby a new behavior or function can be added to the robot (1). Namely, the plurality of behavior modules permits to enable the robot (1) to show a complicated behavior and have units thereof recombined.
    • 提供了一种包括位置行为层(SBL)(58)的机器人(1)。 该SBL(58)形成为树结构的形式,其中多个模式(行为模块)在层级上连接,使得模式对于它们中的每一个独立地彼此高度独立。 专利模式可以定义连接子模式的模式,例如使子模式在其中被执行为唯一的OR类型模式,以及使多个子模式被同时行为的类型模式或SEQUENCE类型 模式,其指示多个子图案应该行为的顺序,从而允许选择机器人(1)的行为模式。 另外,SBL(58)中还可以包括新的子模式,而不需要重写树形结构中的模式连接,从而可以向机器人(1)添加新的行为或功能。 也就是说,多个行为模块允许机器人(1)显示复杂的行为并且其单元重新组合。
    • 7. 发明授权
    • Information processing apparatus, information processing method, and program
    • 信息处理装置,信息处理方法和程序
    • US07499892B2
    • 2009-03-03
    • US11397299
    • 2006-04-04
    • Kazumi AoyamaKatsuki MinaminoHideki Shimomura
    • Kazumi AoyamaKatsuki MinaminoHideki Shimomura
    • G06E1/00G06E3/00G06F15/18G06G7/00G10L15/00G10L15/16G10L15/06G10L15/04
    • G06N3/08G10L15/26
    • An information processing apparatus includes a first learning unit adapted to learn a first SOM (self-organization map), based on a first parameter extracted from an observed value, a winner node determination unit adapted to determine a winner node on the first SOM, a searching unit adapted to search for a generation node on a second SOM having highest connection strength with the winner node, a parameter generation unit adapted to generate a second parameter from the generation node, a modification unit adapted to modify the second parameter generated from the generation node, a first connection weight modification unit adapted to modify the connection weight when end condition is satisfied, a second connection weight modification unit adapted to modify the connection weight depending on evaluation made by a user, and a second learning unit adapted to learn the second SOM based on the second parameter obtained when the end condition is satisfied.
    • 信息处理装置包括:第一学习单元,适于基于从观测值提取的第一参数来学习第一SOM(自组织映射),优胜者节点确定单元,适于确定第一SOM上的胜利者节点; 搜索单元,适于在与所述胜利者节点具有最高连接强度的第二SOM上搜索生成节点;参数生成单元,适于从所述生成节点生成第二参数;修改单元,适于修改从所述生成节点生成的所述第二参数 节点,适于在满足结束条件时修改连接权重的第一连接权重修改单元,适于根据用户进行的评估来修改连接权重的第二连接权重修改单元,以及适于学习第二连接权重修改单元的第二学习单元 基于在满足结束条件时获得的第二参数的SOM。
    • 9. 发明授权
    • Method and apparatus for learning data, method and apparatus for generating data, and computer program
    • 用于学习数据的方法和装置,用于生成数据的方法和装置以及计算机程序
    • US07346595B2
    • 2008-03-18
    • US11396836
    • 2006-04-03
    • Kazumi AoyamaKatsuki MinaminoHideki Shimomura
    • Kazumi AoyamaKatsuki MinaminoHideki Shimomura
    • G06F15/18G06F17/30
    • G05D1/0221Y10S707/99935Y10S707/99936
    • A learning apparatus for learning time series data in a link model including a plurality of input time series pattern storage networks and a plurality of output time series pattern storage networks with nodes of the input time series pattern storage networks linked to nodes of the output time series pattern storage networks, includes a learning unit for updating in a self-organizing manner each of the plurality of input time series pattern storage networks and updating in a self-organizing manner each of the plurality of output time series pattern storage networks and a link relationship updating unit for updating a link relationship between each node of the output time series pattern storage network and an input winner node, and updating a link relationship between each node of the input time series pattern storage network and an output winner node.
    • 一种用于在包括多个输入时间序列模式存储网络和多个输出时间序列模式存储网络的链路模型中学习时间序列数据的学习装置,其具有链接到输出时间序列的节点的输入时间序列模式存储网络的节点 模式存储网络包括学习单元,用于以多个输入时间序列模式存储网络中的每一个以自组织方式更新,并且以自组织方式更新多个输出时间序列模式存储网络中的每一个以及链接关系 更新单元,用于更新输出时间序列模式存储网络的每个节点与输入胜利者节点之间的链路关系,并且更新输入时间序列模式存储网络的每个节点与输出获胜者节点之间的链路关系。