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31. 发明授权

US10049325B2 Information processing to provide entertaining agent for a game character 有权
公开(公告)号：US10049325B2
公开(公告)日：2018-08-14
申请号：US13561704
申请日：2012-07-30
申请人： Hideki Shimomura , Kenta Kawamoto , Kohtaro Sabe
发明人： Hideki Shimomura , Kenta Kawamoto , Kohtaro Sabe
IPC分类号： G06F15/18 , G06N7/00
摘要： Provided is an information processing apparatus including a learning part performing learning of a model of an environment in which an agent performs action, using an observed value observed in the agent when the agent capable of action performs action, an action determining part determining action to be performed by the agent, based on the model, and a user instruction output part outputting instruction information representing an instruction from a user according to the instruction from the user, wherein the action determining part determines the action performed by the agent according to the instruction information when there is an instruction from the user.

32. 发明授权

US09766604B2 Control device, control method, computer program product, and robot control system 有权
公开(公告)号：US09766604B2
公开(公告)日：2017-09-19
申请号：US14234658
申请日：2012-07-25
申请人： Kenta Kawamoto , Yoshiaki Iwai , Satoru Shimizu
发明人： Kenta Kawamoto , Yoshiaki Iwai , Satoru Shimizu
IPC分类号： G06F3/048 , G05B15/02 , G05D1/00 , G06F3/0484
CPC分类号： G05B15/02 , G05B2219/40099 , G05B2219/40123 , G05B2219/40409 , G05B2219/40411 , G05D1/0038 , G05D2201/0217 , G06F3/04842
摘要： A control system, method and computer program product cooperate to assist control for an autonomous robot. The system includes a communications interface that exchanges information with the autonomous robot (22). A user interface displays a scene of location in which the autonomous robot (22) is positioned, and also receives an indication of a user selection of a user selected area within the scene. The communications interface transmits an indication of said user selected area to the autonomous robot (22) for further processing of the area by said autonomous robot (22).

33. 发明授权

US09091564B2 Information processing apparatus, information processing method, and program 有权
标题翻译：信息处理装置，信息处理方法和程序
公开(公告)号：US09091564B2
公开(公告)日：2015-07-28
申请号：US13564205
申请日：2012-08-01
申请人： Kenta Kawamoto , Hirotaka Suzuki
发明人： Kenta Kawamoto , Hirotaka Suzuki
IPC分类号： G05D11/00 , G01D4/00 , G06Q50/06 , H02J3/00
CPC分类号： G01D4/00 , G06Q50/06 , H02J3/00 , H02J2003/003 , H02J2003/007 , Y02B90/245 , Y02E60/76 , Y04S10/54 , Y04S10/60 , Y04S20/38 , Y04S20/40 , Y04S40/22
摘要： There is provided an information processing apparatus including: an appliance power consumption estimating unit estimating power consumption of each of a plurality of appliances disposed inside a large region that is divided into a plurality of regions; an appliance presence probability estimating unit estimating appliance presence probabilities that are probabilities that the respective appliances are present in the respective regions; a responsible share deciding unit deciding responsible shares that are proportions for respective people when power consumption in each region is shared among people who may be present in the large region; and a power consumption allocating unit calculating an allocated amount of power consumption of each person based on the power consumption of each of the plurality of appliances, the appliance presence probabilities, and the responsible shares.
摘要翻译：提供了一种信息处理设备，包括：设备功耗估计单元，估计设置在被划分为多个区域的大区域内的多个设备中的每一个的功耗; 设备存在概率估计单元估计各个设备存在于各个区域中的概率的设备存在概率; 负责任的股份决定单位决定在大区域内的人员之间共享每个地区的电力消耗时各个人的比例的负责人; 以及功耗分配单元，基于所述多个器具中的每一个的功耗，所述器具存在概率和所述负责人的共享来计算每个人的分配的功耗量。

34. 发明授权

US08725510B2 HMM learning device and method, program, and recording medium 有权
标题翻译： HMM学习装置和方法，程序和记录介质
公开(公告)号：US08725510B2
公开(公告)日：2014-05-13
申请号：US12829984
申请日：2010-07-02
申请人： Yukiko Yoshiike , Kenta Kawamoto , Kuniaki Noda , Kohtaro Sabe
发明人： Yukiko Yoshiike , Kenta Kawamoto , Kuniaki Noda , Kohtaro Sabe
IPC分类号： G10L15/14
CPC分类号： G06N99/005
摘要： An HMM (Hidden Markov Model) learning device includes: a learning unit for learning a state transition probability as the function of actions that an agent can execute, with learning with HMM performed based on actions that the agent has executed, and time series information made up of an observation signal; and a storage unit for storing learning results by the learning unit as internal model data including a state-transition probability table and an observation probability table; with the learning unit calculating frequency variables used for estimation calculation of HMM state-transition and HMM observation probabilities; with the storage unit holding the frequency variables corresponding to each of state-transition probabilities and each of observation probabilities respectively, of the state-transition probability table; and with the learning unit using the frequency variables held by the storage unit to perform learning, and estimating the state-transition probability and the observation probability based on the frequency variables.
摘要翻译： HMM（隐马尔可夫模型）学习装置包括：用于学习作为代理可以执行的动作的函数的状态转移概率的学习单元，基于代理已经执行的动作执行的HMM的学习以及作出的时间序列信息观察信号; 以及存储单元，用于将所述学习单元的学习结果存储为包括状态转换概率表和观察概率表的内部模型数据; 学习单元计算用于HMM状态转换和HMM观察概率的估计计算的频率变量; 存储单元保持状态转移概率表中分别对应于状态转换概率和每个观察概率的频率变量; 并且所述学习单元使用由所述存储单元保持的频率变量来执行学习，并且基于所述频率变量来估计所述状态转换概率和观察概率。

35. 发明申请

US20110238213A1 GRIPPING JUDGMENT APPARATUS AND GRIPPING JUDGMENT METHOD 有权
标题翻译：拖运裁判设备和拖车裁判方法
公开(公告)号：US20110238213A1
公开(公告)日：2011-09-29
申请号：US13023797
申请日：2011-02-09
申请人： Kenichiro Nagasaka , Toshimitsu Tsuboi , Atsushi Miyamoto , Yasunori Kawanami , Tetsuharu Fukushima , Kenta Kawamoto
发明人： Kenichiro Nagasaka , Toshimitsu Tsuboi , Atsushi Miyamoto , Yasunori Kawanami , Tetsuharu Fukushima , Kenta Kawamoto
IPC分类号： B25J13/08
CPC分类号： B25J9/1612
摘要： There is provided a gripping judgment apparatus including a plan unit that generates a target orbit for moving a gripping unit in a state in which an object as a gripping target is gripped by the gripping unit, an observation unit that measures movement of the gripping unit driven based on the target orbit, a gripping state judgment unit that judges whether or not an object as a gripping target is grippable based on a target value of the gripping unit derived from the target orbit and an actual measured value measured by the observation unit, and a gripping state change unit that changes a gripping state of an object gripped by the gripping unit based on a judgment result obtained by the gripping state judgment unit.
摘要翻译：提供了一种夹持判断装置，包括：平面单元，其在作为夹持目标的物体被夹持单元夹持的状态下产生用于移动夹持单元的目标轨道;观察单元，其测量夹持单元驱动的运动基于所述目标轨道的夹持状态判断单元，基于来自所述目标轨道的所述夹持单元的目标值和由所述观测单元测量的实际测量值，判断作为夹持目标的物体是否可抓握，以及夹持状态改变单元，其基于由夹持状态判断单元获得的判断结果，改变由夹持单元夹持的物体的夹持状态。

36. 发明申请

US20110234758A1 ROBOT DEVICE AND METHOD OF CONTROLLING ROBOT DEVICE 有权
标题翻译：机器人装置和控制机器人装置的方法
公开(公告)号：US20110234758A1
公开(公告)日：2011-09-29
申请号：US13070066
申请日：2011-03-23
申请人： Toshimitsu TSUBOI , Kenta Kawamoto , Yasunori Kawanami , Atsushi Miyamoto
发明人： Toshimitsu TSUBOI , Kenta Kawamoto , Yasunori Kawanami , Atsushi Miyamoto
IPC分类号： H04N13/02
CPC分类号： H04N13/254
摘要： There is provided a robot device including an irradiation unit that irradiates pattern light to an external environment, an imaging unit that acquires an image by imaging the external environment, an external environment recognition unit that recognizes the external environment, an irradiation determining unit that controls the irradiation unit to be turned on when it is determined that irradiation of the pattern light is necessary based on an acquisition status of the image, and a light-off determining unit that controls the irradiation unit to be turned off when it is determined that irradiation of the pattern light is unnecessary or that irradiation of the pattern light is necessary to be forcibly stopped, based on the external environment.
摘要翻译：提供了一种机器人装置，其包括：将图案光照射到外部环境的照射单元，通过对外部环境进行摄像而获取图像的摄像单元，识别外部环境的外部环境识别单元，照射判定单元，基于图像的获取状态确定需要照射图案光的照射单元，以及当确定照射单元被照射时控制照射单元被关闭的点灯确定单元基于外部环境，不需要图案光或者模式光的照射被强制停止。

37. 发明申请

US20110010176A1 HMM LEARNING DEVICE AND METHOD, PROGRAM, AND RECORDING MEDIUM 有权
标题翻译： HMM学习设备和方法，程序和记录介质
公开(公告)号：US20110010176A1
公开(公告)日：2011-01-13
申请号：US12829984
申请日：2010-07-02
申请人： Yukiko YOSHIIKE , Kenta Kawamoto , Kuniaki Noda , Kohtaro Sabe
发明人： Yukiko YOSHIIKE , Kenta Kawamoto , Kuniaki Noda , Kohtaro Sabe
IPC分类号： G10L15/14
CPC分类号： G06N99/005
摘要： An HMM (Hidden Markov Model) learning device includes: a learning unit for learning a state transition probability as the function of actions that an agent can execute, with learning with HMM performed based on actions that the agent has executed, and time series information made up of an observation signal; and a storage unit for storing learning results by the learning unit as internal model data including a state-transition probability table and an observation probability table; with the learning unit calculating frequency variables used for estimation calculation of HMM state-transition and HMM observation probabilities; with the storage unit holding the frequency variables corresponding to each of state-transition probabilities and each of observation probabilities respectively, of the state-transition probability table; and with the learning unit using the frequency variables held by the storage unit to perform learning, and estimating the state-transition probability and the observation probability based on the frequency variables.
摘要翻译： HMM（隐马尔可夫模型）学习装置包括：用于学习作为代理可以执行的动作的函数的状态转移概率的学习单元，基于代理已经执行的动作执行的HMM的学习以及作出的时间序列信息观察信号; 以及存储单元，用于将所述学习单元的学习结果存储为包括状态转换概率表和观察概率表的内部模型数据; 学习单元计算用于HMM状态转换和HMM观察概率的估计计算的频率变量; 存储单元保持状态转移概率表中分别对应于状态转换概率和每个观察概率的频率变量; 并且所述学习单元使用由所述存储单元保持的频率变量来执行学习，并且基于所述频率变量来估计所述状态转换概率和观察概率。

38. 发明申请

US20100318478A1 INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM 审中-公开
标题翻译：信息处理设备，信息处理方法和程序
公开(公告)号：US20100318478A1
公开(公告)日：2010-12-16
申请号：US12791240
申请日：2010-06-01
申请人： Yukiko Yoshiike , Kenta Kawamoto , Kuniaki Noda , Kohtaro Sabe
发明人： Yukiko Yoshiike , Kenta Kawamoto , Kuniaki Noda , Kohtaro Sabe
IPC分类号： G06N5/02 , G06F15/18
CPC分类号： G06N3/006 , G06K9/00335 , G06K9/00664 , G06K9/6297
摘要： An information processing device includes: a calculating unit configured to calculate a current-state series candidate that is a state series for an agent capable of actions reaching the current state, based on a state transition probability model obtained by performing learning of the state transition probability model stipulated by a state transition probability that a state will be transitioned according to each of actions performed by an agent capable of actions, and an observation probability that a predetermined observation value will be observed from the state, using an action performed by the agent, and an observation value observed at the agent when the agent performs an action; and a determining unit configured to determine an action to be performed next by the agent using the current-state series candidate in accordance with a predetermined strategy.
摘要翻译：一种信息处理设备，包括：计算单元，被配置为基于通过执行状态转移概率的学习获得的状态转移概率模型来计算作为达到当前状态的动作的代理的状态序列的当前状态序列候选由状态转移概率规定的模式，其状态将根据由能够执行动作的代理执行的动作而转变，并且使用由代理执行的动作从该状态观察到预定观察值的观察概率，以及当代理人执行动作时在代理处观察到的观察值; 以及确定单元，被配置为根据预定策略来确定所述代理使用所述当前状态序列候选来执行的动作。

39. 发明授权

US07840508B2 Information processing apparatus, information processing method, and program 失效
标题翻译：信息处理装置，信息处理方法和程序
公开(公告)号：US07840508B2
公开(公告)日：2010-11-23
申请号：US11732807
申请日：2007-04-04
申请人： Yukiko Yoshiike , Masato Ito , Katsuki Minamino , Hirotaka Suzuki , Kenta Kawamoto
发明人： Yukiko Yoshiike , Masato Ito , Katsuki Minamino , Hirotaka Suzuki , Kenta Kawamoto
IPC分类号： G06F15/18 , G06N3/08
CPC分类号： G06N3/02
摘要： An information processing apparatus includes a storage unit configured to store a node holding dynamics; an input-weight-coefficient adjuster configured to adjust input-weight coefficients on a dimension-by-dimension basis, the input-weight coefficients being weight coefficients for individual dimensions of input data input to input units of the node, the input data being observed time-series data having a plurality of dimensions; and an output-weight-coefficient adjuster configured to adjust output-weight coefficients on a dimension-by-dimension basis, the output-weight coefficients being weight coefficients for individual dimensions of output data having a plurality of dimensions and output from output units of the node.
摘要翻译：一种信息处理装置，包括：存储单元，被配置为存储保存动态的节点; 输入权重系数调整器，其被配置为在逐个维度的基础上调整输入权重系数，输入权重系数是输入到节点的输入单元的输入数据的各个维度的权重系数，观察到的输入数据具有多个维度的时间序列数据; 以及输出权重系数调整器，其被配置为在逐个维度的基础上调整输出权重系数，所述输出权重系数是具有多个维度的输出数据的各个维度的权重系数，并且从所述输出单元的输出单元输出节点。

40. 发明授权

US07587069B2 Weak hypothesis generation apparatus and method, learning apparatus and method, detection apparatus and method, facial expression learning apparatus and method, facial expression recognition apparatus and method, and robot apparatus 有权
公开(公告)号：US07587069B2
公开(公告)日：2009-09-08
申请号：US12075080
申请日：2008-03-07
申请人： Javier R. Movellan , Marian S. Bartlett , Gwendolen C. Littlewort , John Hershey , Ian R. Fasel , Eric C. Carlson , Josh Susskind , Kohtaro Sabe , Kenta Kawamoto , Kenichi Hidai
发明人： Javier R. Movellan , Marian S. Bartlett , Gwendolen C. Littlewort , John Hershey , Ian R. Fasel , Eric C. Carlson , Josh Susskind , Kohtaro Sabe , Kenta Kawamoto , Kenichi Hidai
IPC分类号： G06K9/00
CPC分类号： G06K9/00248 , G06K9/00308 , G06K9/6256 , G06N3/004
摘要： A facial expression recognition system that uses a face detection apparatus realizing efficient learning and high-speed detection processing based on ensemble learning when detecting an area representing a detection target and that is robust against shifts of face position included in images and capable of highly accurate expression recognition, and a learning method for the system, are provided. When learning data to be used by the face detection apparatus by Adaboost, processing to select high-performance weak hypotheses from all weak hypotheses, then generate new weak hypotheses from these high-performance weak hypotheses on the basis of statistical characteristics, and select one weak hypothesis having the highest discrimination performance from these weak hypotheses, is repeated to sequentially generate a weak hypothesis, and a final hypothesis is thus acquired. In detection, using an abort threshold value that has been learned in advance, whether provided data can be obviously judged as a non-face is determined every time one weak hypothesis outputs the result of discrimination. If it can be judged so, processing is aborted. A predetermined Gabor filter is selected from the detected face image by an Adaboost technique, and a support vector for only a feature quantity extracted by the selected filter is learned, thus performing expression recognition.

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