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    • 62. 发明授权
    • Robot apparatus and robot apparatus motion control method
    • 机器人装置和机器人装置运动控制方法
    • US06697708B2
    • 2004-02-24
    • US10149825
    • 2002-09-24
    • Tsuyoshi TakagiKohtaro SabeTakayuki SakamotoKazufumi Oyama
    • Tsuyoshi TakagiKohtaro SabeTakayuki SakamotoKazufumi Oyama
    • G06F1900
    • G06N3/008A63H30/04G05B19/4062G05B2219/34396
    • A robot apparatus includes a command controller (101) for outputting an output command associated with an input command, management units (102), (103) and (104) for outputting data associated with the commands output by the command controller (101), a command transmitter (105) for controlling the transmission of the data output by the management units (102), (103) and (104) and controllers (106), (107) and (108) for controlling action units (109), (110) and (111), such as a motor, based on data output by the command transmitter (105). The command transmitter (105) sends the action control data for synchronization, output by the management units (102), (103) and (104), in synchroneity to the action units (109), (110) and (111).
    • 机器人装置包括用于输出与输入命令相关联的输出命令的命令控制器(101),用于输出与命令控制器(101)输出的命令相关联的数据的管理单元(102),(103)和(104) 用于控制由管理单元(102),(103)和(104)输出的数据的传输的命令发送器(105)和用于控制动作单元(109)的控制器(106),(107)和(108) (110)和(111),诸如电动机,基于命令发射器(105)输出的数据。 命令发送器(105)将用于同步的动作控制数据发送到动作单元(109),(110)和(111),由管理单元(102),(103)和(104)以同步方式输出。
    • 63. 发明授权
    • Data processing device that calculates an arrival probability for a destination using a user's movement history including a missing portion
    • 数据处理装置,其使用包括缺失部分的用户的移动历史来计算目的地的到达概率
    • US09589082B2
    • 2017-03-07
    • US13878920
    • 2011-11-07
    • Naoki IdeMasato ItoKohtaro Sabe
    • Naoki IdeMasato ItoKohtaro Sabe
    • G06F17/50G01C21/34G01C21/36G08G1/01G06F17/18G01S5/00G06N99/00
    • G06F17/5009G01C21/3484G01C21/3617G01S5/0009G06F17/18G06F17/50G06N99/005G08G1/0129
    • The present invention relates to a data processing device, a data processing method, and a program which enable prediction to be performed even when there is a gap in the current location data to be obtained in real time. A learning main processor 23 represents movement history data serving as data for learning, as a probability model which represents a user's activity, and obtains a parameter thereof. A prediction main processor 33 uses the probability model obtained by learning to estimate a user's current location from movement history data to be obtained in real time. In the event that there is a data missing portion included in movement history data to be obtained in real time, the prediction main processor 33 generates the data missing portion thereof by interpolation processing, and estimates state nose series corresponding to the interpolated data for prediction. With estimation of state node series, an observation probability less contribution of data than actual data is employed regarding interpolated data. The present invention may be applied to a data processing device configured to predict a destination from movement history data, for example.
    • 数据处理装置,数据处理方法和程序技术领域本发明涉及即使在实时获取的当前位置数据存在间隙的情况下也能进行预测的数据处理装置,数据处理方法和程序。 学习主处理器23表示作为用于学习的数据的运动历史数据,作为表示用户的活动的概率模型,并且获得其参数。 预测主处理器33使用通过学习获得的概率模型来实时地获得的移动历史数据来估计用户的当前位置。 在要实时获取的移动历史数据中包含数据缺失部分的情况下,预测主处理器33通过内插处理生成其数据缺失部分,并且估计与用于预测的内插数据相对应的状态鼻序列。 通过估计状态节点序列,对于内插数据采用数据比实际数据更少的观测概率。 本发明可以应用于例如被配置为从移动历史数据预测目的地的数据处理装置。
    • 64. 发明授权
    • Information processing device, information processing method, and program
    • 信息处理装置,信息处理方法和程序
    • US09285235B2
    • 2016-03-15
    • US14005648
    • 2012-03-16
    • Naoki IdeYoshiyuki KobayashiMasato ItoKohtaro Sabe
    • Naoki IdeYoshiyuki KobayashiMasato ItoKohtaro Sabe
    • G01C21/00G01C21/36G01C21/34G06N5/00
    • G01C21/3617G01C21/3484
    • The present technique relates to an information processing device, an information processing method and a program which can accumulate sufficient movement history data with a little power consumption. A similarity search unit searches for a past route similar to the immediate movement history which is acquired by a position sensor unit and which has time series position data, from the search data stored in a past history DB. A fitness determination unit determines whether or not goodness of fit of the past route searched by the similarity search unit and the immediate movement history is a predetermined threshold or more. A sensor control unit controls an acquisition interval of the position data of the position sensor unit according to a determination result of the fitness determination unit. The technique of this disclosure is applicable to a prediction device which, for example, acquires position data and predicts a predicted route.
    • 本技术涉及一种信息处理装置,信息处理方法和程序,其能够以少量功耗累积足够的运动历史数据。 相似度搜索单元从存储在过去历史DB中的搜索数据中搜索类似于由位置传感器单元获取并具有时间序列位置数据的即时移动历史的过去路线。 适应度确定单元确定由相似性搜索单元搜索的过去路线的适合度和即时移动历史是否为预定阈值以上。 传感器控制单元根据适应度判定单元的确定结果控制位置传感器单元的位置数据的采集间隔。 本公开的技术可应用于例如获取位置数据并预测预测路线的预测装置。
    • 65. 发明申请
    • DATA PROCESSING DEVICE, DATA PROCESSING METHOD, AND PROGRAM
    • 数据处理设备,数据处理方法和程序
    • US20130197890A1
    • 2013-08-01
    • US13878920
    • 2011-11-07
    • Naoki IdeMasato ItoKohtaro Sabe
    • Naoki IdeMasato ItoKohtaro Sabe
    • G06F17/50
    • G06F17/5009G01C21/3484G01C21/3617G01S5/0009G06F17/18G06F17/50G06N99/005G08G1/0129
    • The present invention relates to a data processing device, a data processing method, and a program which enable prediction to be performed even when there is a gap in the current location data to be obtained in real time. A learning main processor 23 represents movement history data serving as data for learning, as a probability model which represents a user's activity, and obtains a parameter thereof. A prediction main processor 33 uses the probability model obtained by learning to estimate a user's current location from movement history data to be obtained in real time. In the event that there is a data missing portion included in movement history data to be obtained in real time, the prediction main processor 33 generates the data missing portion thereof by interpolation processing, and estimates state nose series corresponding to the interpolated data for prediction. With estimation of state node series, an observation probability less contribution of data than actual data is employed regarding interpolated data. The present invention may be applied to a data processing device configured to predict a destination from movement history data, for example.
    • 数据处理装置,数据处理方法和程序技术领域本发明涉及即使在实时获取的当前位置数据存在间隙的情况下也能进行预测的数据处理装置,数据处理方法和程序。 学习主处理器23表示作为用于学习的数据的运动历史数据,作为表示用户的活动的概率模型,并且获得其参数。 预测主处理器33使用通过学习获得的概率模型来实时地获得的移动历史数据来估计用户的当前位置。 在要实时获取的移动历史数据中包含数据缺失部分的情况下,预测主处理器33通过内插处理生成其数据缺失部分,并且估计与用于预测的内插数据相对应的状态鼻序列。 通过估计状态节点序列,对于内插数据采用数据比实际数据更少的观测概率。 本发明可以应用于例如被配置为从移动历史数据预测目的地的数据处理装置。
    • 67. 发明申请
    • DATA PROCESSING DEVICE, DATA PROCESSING METHOD, AND PROGRAM
    • 数据处理设备,数据处理方法和程序
    • US20110302116A1
    • 2011-12-08
    • US13116940
    • 2011-05-26
    • Naoki IdeMasato ItoKohtaro Sabe
    • Naoki IdeMasato ItoKohtaro Sabe
    • G06F15/18
    • G08G1/096844G01C21/3484G06N20/00
    • A data processing device including a learning section which expresses user movement history data obtained as learning data as a probability model which expresses activities of a user and learns parameters of the model; a destination and stopover estimation section which estimates a destination node and a stopover node from state nodes of the probability model; a current location estimation section which inputs the user movement history data in the probability model and estimates a current location node which is equivalent to the current location of the user; a searching section which searches for a route from the current location of the user to a destination using information on the estimated destination node and stopover node and the current location node and the probability model obtained by learning; and a calculating section which calculates an arrival probability and a necessary time to the searched destination.
    • 一种数据处理装置,包括学习部,其将作为学习数据获取的用户移动历史数据表示为表示用户的活动并学习模型的参数的概率模型; 目的地和中途停留估计部,其从所述概率模型的状态节点估计目的地节点和中途停止节点; 当前位置估计部分,其输入概率模型中的用户移动历史数据,并估计与当前用户的当前位置相当的当前位置节点; 搜索部,其使用关于所估计的目的地节点和中继节点以及当前位置节点的信息和通过学习获得的概率模型来搜索从用户的当前位置到目的地的路线; 以及计算部分,其计算到所搜索到的目的地的到达概率和必要时间。
    • 69. 发明申请
    • DATA PROCESSING APPARATUS, DATA PROCESSING METHOD, AND PROGRAM
    • 数据处理设备,数据处理方法和程序
    • US20110060709A1
    • 2011-03-10
    • US12874553
    • 2010-09-02
    • Naoki IdeMasato ItoKohtaro Sabe
    • Naoki IdeMasato ItoKohtaro Sabe
    • G06F15/18
    • G01C21/3484
    • A data processing apparatus includes an action learning unit configured to train a user activity model representing activity states of a user in the form of a probabilistic state transition model using time-series location data items of the user, an action recognizing unit configured to recognize a current location of the user using the user activity model obtained through the action learning unit, an action estimating unit configured to estimate a possible route for the user from the current location recognized by the action recognizing unit and a selection probability of the route, and a travel time estimating unit configured to estimate an arrival probability of the user arriving at a destination and a travel time to the destination using the estimated route and the estimated selection probability.
    • 一种数据处理装置,包括动作学习单元,被配置为使用表示使用者的时间序列位置数据项的概率状态转换模型的形式表示用户的活动状态的用户活动模型,动作识别单元, 使用通过动作学习单元获取的用户活动模型的用户的当前位置,动作估计单元,被配置为从动作识别单元识别的当前位置和路线的选择概率来估计用户的可能路线,以及 旅行时间估计单元,被配置为使用所估计的路线和估计的选择概率来估计到达目的地的用户的到达概率和到达目的地的行进时间。
    • 70. 发明授权
    • Image recognition device using feature points, method for recognizing images using feature points, and robot device which recognizes images using feature points
    • 使用特征点的图像识别装置,使用特征点识别图像的方法,以及使用特征点识别图像的机器人装置
    • US07627178B2
    • 2009-12-01
    • US10517615
    • 2004-04-22
    • Hirotaka SuzukiKohtaro SabeMasahiro Fujita
    • Hirotaka SuzukiKohtaro SabeMasahiro Fujita
    • G06K9/46
    • G06K9/6212G06K9/4609G06K9/6211G06T7/73
    • In an image recognition apparatus, feature point extraction sections and extract feature points from a model image and an object image. Feature quantity retention sections extract a feature quantity for each of the feature points and retain them along with positional information of the feature points. A feature quantity comparison section compares the feature quantities with each other to calculate the similarity or the dissimilarity and generates a candidate-associated feature point pair having a high possibility of correspondence. A model attitude estimation section repeats an operation of projecting an affine transformation parameter determined by three pairs randomly selected from the candidate-associated feature point pair group onto a parameter space. The model attitude estimation section assumes each member in a cluster having the largest number of members formed in the parameter space to be an inlier. The model attitude estimation section finds the affine transformation parameter according to the least squares estimation using the inlier and outputs a model attitude determined by this affine transformation parameter.
    • 在图像识别装置中,特征点提取部分并从模型图像和对象图像中提取特征点。 特征量保留部分提取每个特征点的特征量,并将其与特征点的位置信息一起保留。 特征量比较部分将特征量彼此进行比较以计算相似度或相似性,并生成具有高对应可能性的候选相关特征点对。 模型姿态估计部重复将从候选关联特征点对组中随机选择的三对决定的仿射变换参数投影到参数空间的动作。 模型姿态估计部分假设在参数空间中形成的具有最大数量的成员的群组中的每个成员是一个较早的。 模型姿态估计部根据使用该误差的最小二乘估计求出仿射变换参数,并输出由该仿射变换参数确定的模型姿态。