公开(公告)号：US07437214B2

公开(公告)日：2008-10-14

申请号：US10515854

申请日：2004-03-24

申请人： Kohtaro Sabe ,  Takeshi Ohashi ,  Kenta Kawamoto

发明人： Kohtaro Sabe ,  Takeshi Ohashi ,  Kenta Kawamoto

IPC分类号： G06F19/00

CPC分类号： B62D57/032

摘要： A legged mobile robot can calculate the movement amount between a portion of the robot apparatus that had been in contact with a floor up to now and a next portion of the robot apparatus in contact with the floor using kinematics and to switch transformation to a coordinate system serving as an observation reference as a result of the switching between the floor contact portions.

摘要翻译： 腿式移动机器人可以计算出与现在的地板接触的机器人装置的一部分与使用运动学与地板接触的机器人装置的下一部分之间的移动量，并将变换切换到坐标系 作为地板接触部之间的切换的结果作为观察参考。

公开(公告)号：US07386163B2

公开(公告)日：2008-06-10

申请号：US10387647

申请日：2003-03-13

申请人： Kohtaro Sabe ,  Kenta Kawamoto ,  Takeshi Ohashi ,  Masaki Fukuchi ,  Atsushi Okubo ,  Steffen Gutmann

发明人： Kohtaro Sabe ,  Kenta Kawamoto ,  Takeshi Ohashi ,  Masaki Fukuchi ,  Atsushi Okubo ,  Steffen Gutmann

IPC分类号： G06K9/00 ,  H04N15/00 ,  H04N7/00 ,  H04N7/18 ,  G06F19/00 ,  G06F17/10 ,  G01C22/00

CPC分类号： G06K9/00664 ,  G06T7/97

摘要： An obstacle recognition apparatus is provided which can recognize an obstacle by accurately extracting a floor surface. It includes a distance image generator (222) to produce a distance image using a disparity image and homogeneous transform matrix, a plane detector (223) to detect plane parameters on the basis of the distance image from the distance image generator (222), a coordinate transformer (224) to transform the homogeneous transform matrix into a coordinate of a ground-contact plane of a robot apparatus (1), and a floor surface detector (225) to detect a floor surface using the plane parameters from the plane detector (223) and result of coordinate transformation from the coordinate transformer (224) and supply the plane parameters to an obstacle recognition block (226). The obstacle recognition block (226) selects one of points on the floor surface using the plane parameters of the floor surface detected by the floor surface detector (225) and recognizes an obstacle on the basis of the selected point.

摘要翻译： 提供了能够通过精确地提取地板面来识别障碍物的障碍物识别装置。 它包括使用视差图像和均匀变换矩阵产生距离图像的距离图像生成器（222），基于距离图像生成器（222）的距离图像检测平面参数的平面检测器（223）， 将所述均匀变换矩阵变换为机器人装置（1）的接地面的坐标的坐标变换器（224）和使用来自所述平面检测器的平面参数来检测地板面的地板面检测器（225） 223）和从坐标变换器（224）的坐标变换的结果，并将平面参数提供给障碍物识别块（226）。 障碍物识别块（226）使用由地板表面检测器（225）检测到的地板表面的平面参数来选择地板表面上的一个点，并基于所选择的点识别障碍物。

公开(公告)号：US20050222709A1

公开(公告)日：2005-10-06

申请号：US10515854

申请日：2004-03-24

申请人： Kohtaro Sabe ,  Takeshi Ohashi ,  Kenta Kawamoto

发明人： Kohtaro Sabe ,  Takeshi Ohashi ,  Kenta Kawamoto

IPC分类号： B25J13/08 ,  B62D57/032 ,  G06F19/00

CPC分类号： B62D57/032

摘要： The present invention is applied to, for example, a legged mobile robot and makes it possible to calculate the movement amount between a portion of the robot apparatus that had been in contact with a floor up to now and a next portion of the robot apparatus in contact with the floor using kinematics and to switch transformation to a coordinate system serving as an observation reference as a result of the switching between the floor contact portions.

摘要翻译： 本发明应用于例如腿式移动机器人，并且可以计算到现在与现在的地板接触的机器人装置的一部分与机器人装置的下一部分之间的移动量 使用运动学与地板接触，并且由于地板接触部分之间的切换而将变换切换到用作观测参考的坐标系。

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.

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。

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。

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。

公开(公告)号：US07369686B2

公开(公告)日：2008-05-06

申请号：US10399740

申请日：2002-08-21

申请人： Jun Yokono ,  Kohtaro Sabe ,  Kenta Kawamoto

发明人： Jun Yokono ,  Kohtaro Sabe ,  Kenta Kawamoto

IPC分类号： G06K9/00

CPC分类号： G06K9/00288 ,  G06K9/00221 ,  G06K9/00228

摘要： A robot includes a face extracting section for extracting features of a face included in an image captured by a CCD camera, and a face recognition section for recognizing the face based on a result of face extraction by the face extracting section. The face extracting section is implemented by Gabor filters that filter images using a plurality of filters that have orientation selectivity and that are associated with different frequency components. The face recognition section is implemented by a support vector machine that maps the result of face recognition to a non-linear space and that obtains a hyperplane that separates in that space to discriminate a face from a non-face. The robot is allowed to recognize a face of a user within a predetermined time under a dynamically changing environment.

摘要翻译： 机器人包括：面部提取部，用于提取由CCD照相机拍摄的图像中包含的面部的特征;以及面部识别部，其基于面部提取部的面部提取的结果识别脸部。 人脸提取部分由Gabor滤波器实现，该滤波器使用具有取向选择性并且与不同频率分量相关联的多个滤波器对图像进行滤波。 脸部识别部分由支持向量机实现，该支持向量机将人脸识别的结果映射到非线性空间，并获得在该空间中分离的超平面，以将脸部与非脸部区分开。 允许机器人在动态变化的环境下在预定时间内识别用户的脸部。

公开(公告)号：US07228201B2

公开(公告)日：2007-06-05

申请号：US10110497

申请日：2001-08-16

申请人： Kohtaro Sabe ,  Kenta Kawamoto

发明人： Kohtaro Sabe ,  Kenta Kawamoto

IPC分类号： G06F19/00

CPC分类号： G06F9/544 ,  G05B19/4187 ,  G06F9/546 ,  G06N3/008 ,  Y02P90/205

摘要： A robot device (1) has a central processing process (CPU) having a plurality of objects and adapted for carrying out control processing on the basis inter-object communication carried out between the objects, the central processing process controlling accesses by the plurality of objects to a shared memory shared by the plurality of objects and thus carrying out inter-object communication. Specifically, the central processing process generates pointers P11, P12, P13, P21, P22 in accordance with accesses by the objects to predetermined areas M1, M2 on a shared memory M, then measures the pointers by the corresponding number-of-reference measuring objects RO1, RO2, and controls the accesses in accordance with the number of pointers measured, thereby carrying out inter-object communication. This enables easy realization of smooth inter-process communication.

摘要翻译： 机器人装置（1）具有具有多个对象的中央处理处理（CPU），并且适于在对象之间进行的基于对象间通信的基础上进行控制处理，中央处理处理控制多个对象的访问 到由多个对象共享的共享存储器，从而进行对象间通信。 具体地，中央处理处理根据对象对共享存储器M上的预定区域M 1，M 2的访问来生成指针P 11，P 12，P 13，P 21，P 22，然后通过相应的 基准测量对象RO 1，RO 2，并且根据所测量的指针的数量控制访问，从而进行对象间通信。 这使得能够容易地实现平滑的进程间通信。

公开(公告)号：US06862497B2

公开(公告)日：2005-03-01

申请号：US10343525

申请日：2002-06-03

申请人： Thomas Kemp ,  Ralf Kompe ,  Raquel Tato ,  Masahiro Fujita ,  Katsuki Minamino ,  Kenta Kawamoto ,  Rika Horinaka

发明人： Thomas Kemp ,  Ralf Kompe ,  Raquel Tato ,  Masahiro Fujita ,  Katsuki Minamino ,  Kenta Kawamoto ,  Rika Horinaka

IPC分类号： B62D57/02 ,  B62D57/032 ,  G05B13/02 ,  G05B19/042 ,  G05B15/00 ,  G05B19/33

CPC分类号： G05B19/042 ,  B62D57/02 ,  B62D57/032 ,  G05B13/0265

摘要： There is proposed a method that may be universally used for controlling a man-machine interface unit. A learning sample is used in order at least to derive and/or initialize a target action (t) to be carried out and to lead the user from an optional current status (ec) to an optional desired target status (et) as the final status (ef). This learning sample (l) is formed by a data triple made up by an initial status (ei) before an optional action (a) carried out by the user, a final status (ef) after the action taken place (a).

摘要翻译： 提出了可以普遍地用于控制人机接口单元的方法。 至少使用学习样本来导出和/或初始化要执行的目标动作（t），并且将用户从可选的当前状态（ec）引导到可选的期望目标状态（et），作为最终的 状态（ef）。 该学习样本（l）由在用户执行的可选动作（a）之前由初始状态（ei）组成的数据三进制形成，（a）动作之后的最终状态（ef）。