Position estimation device, position estimation method, and program
    1.
    发明授权
    Position estimation device, position estimation method, and program 有权
    位置估计装置,位置估计方法和程序

    公开(公告)号:US09098744B2

    公开(公告)日:2015-08-04

    申请号:US13698572

    申请日:2011-02-10

    IPC分类号: G06K9/48 G06K9/00 G06T7/00

    摘要: Disclosed is a position estimation device including a feature extraction unit that extracts invariant features from an input image, a matching unit that obtains matching between an input image and a registered place by referring to a database containing each registered place and invariant features in association, a similarity calculation unit that calculates a similarity with inclusion of a registered place near a selected registered place when the matching is a threshold or more, and a position identification unit that identifies the input image as a registered place when the similarity is a threshold or more. The feature extraction unit extracts local features from each input image being sequential images taken sequentially, selects features matched between the sequential images as sequential features, and calculates invariant features based on the sequential features. The number of sequential images is variable depending on the number of matched features.

    摘要翻译: 公开了一种位置估计装置,其包括从输入图像中提取不变特征的特征提取单元,通过参照包含关联的每个登记地点和不变特征的数据库,获得输入图像与登记地点之间的匹配的匹配单元, 相似度计算单元,当所述匹配是阈值以上时,计算包含所选登记地点附近的登记地点的相似度;以及位置识别单元,当所述相似度为阈值以上时,将所述输入图像识别为登记地点。 特征提取单元从每个输入图像中提取作为顺序拍摄的顺序图像的局部特征,选择在顺序图像之间匹配的特征作为顺序特征,并且基于顺序特征来计算不变特征。 顺序图像的数量根据匹配的特征数量而变化。

    Position Estimation Device, Position Estimation Method, And Program
    2.
    发明申请
    Position Estimation Device, Position Estimation Method, And Program 有权
    位置估计装置,位置估计方法和程序

    公开(公告)号:US20130108172A1

    公开(公告)日:2013-05-02

    申请号:US13698572

    申请日:2011-02-10

    IPC分类号: G06K9/00

    摘要: Disclosed is a position estimation device including a feature extraction unit that extracts invariant features from an input image, a matching unit that obtains matching between an input image and a registered place by referring to a database containing each registered place and invariant features in association, a similarity calculation unit that calculates a similarity with inclusion of a registered place near a selected registered place when the matching is a threshold or more, and a position identification unit that identifies the input image as a registered place when the similarity is a threshold or more. The feature extraction unit extracts local features from each input image being sequential images taken sequentially, selects features matched between the sequential images as sequential features, and calculates invariant features based on the sequential features. The number of sequential images is variable depending on the number of matched features.

    摘要翻译: 公开了一种位置估计装置,其包括从输入图像中提取不变特征的特征提取单元,通过参照包含关联的每个登记地点和不变特征的数据库,获得输入图像与登记地点之间的匹配的匹配单元, 相似度计算单元,当所述匹配是阈值以上时,计算包含所选登记地点附近的登记地点的相似度;以及位置识别单元,当所述相似度为阈值以上时,将所述输入图像识别为登记地点。 特征提取单元从每个输入图像中提取作为顺序拍摄的顺序图像的局部特征,选择在顺序图像之间匹配的特征作为顺序特征,并且基于顺序特征来计算不变特征。 顺序图像的数量根据匹配的特征数量而变化。

    MAP GENERATION APPARATUS, MAP GENERATION METHOD, MOVING METHOD FOR MOVING BODY, AND ROBOT APPARATUS
    3.
    发明申请
    MAP GENERATION APPARATUS, MAP GENERATION METHOD, MOVING METHOD FOR MOVING BODY, AND ROBOT APPARATUS 有权
    地图生成装置,地图生成方法,移动体的移动方法和机器人装置

    公开(公告)号:US20130216098A1

    公开(公告)日:2013-08-22

    申请号:US13824855

    申请日:2011-08-30

    IPC分类号: G06K9/00

    摘要: Performing map construction under a crowded environment where there are a lot of people. It includes a successive image acquisition unit that obtains images that are taken while a robot is moving, a local feature quantity extraction unit that extracts a quantity at each feature point from the images, a feature quantity matching unit that performs matching among the quantities in the input images, where quantities are extracted by the extraction unit, an invariant feature quantity calculation unit that calculates an average of the matched quantities among a predetermined number of images by the matching unit as an invariant feature quantity, a distance information acquisition unit that calculates distance information corresponding to each invariant feature quantity based on a position of the robot at times when the images are obtained, and a map generation unit that generates a local metrical map as a hybrid map.

    摘要翻译: 在有很多人的拥挤的环境下进行地图建设。 它包括连续图像获取单元,其获得在机器人移动期间拍摄的图像;局部特征量提取单元,从图像中提取每个特征点处的数量;特征量匹配单元, 输入图像,其中通过提取单元提取量;不变特征量计算单元,其通过匹配单元计算预定数量的图像中的匹配量的平均值作为不变特征量;距离信息获取单元,其计算距离 基于在获取图像时的机器人的位置对应于每个不变特征量的信息,以及生成本地计量图作为混合图的地图生成单元。

    Map generation apparatus, map generation method, moving method for moving body, and robot apparatus
    4.
    发明授权
    Map generation apparatus, map generation method, moving method for moving body, and robot apparatus 有权
    地图生成装置,地图生成方法,移动体的移动方法和机器人装置

    公开(公告)号:US09224043B2

    公开(公告)日:2015-12-29

    申请号:US13824855

    申请日:2011-08-30

    摘要: Performing map construction under a crowded environment where there are a lot of people. It includes a successive image acquisition unit that obtains images that are taken while a robot is moving, a local feature quantity extraction unit that extracts a quantity at each feature point from the images, a feature quantity matching unit that performs matching among the quantities in the input images, where quantities are extracted by the extraction unit, an invariant feature quantity calculation unit that calculates an average of the matched quantities among a predetermined number of images by the matching unit as an invariant feature quantity, a distance information acquisition unit that calculates distance information corresponding to each invariant feature quantity based on a position of the robot at times when the images are obtained, and a map generation unit that generates a local metrical map as a hybrid map.

    摘要翻译: 在有很多人的拥挤的环境下进行地图建设。 它包括连续图像获取单元,其获得在机器人移动期间拍摄的图像;局部特征量提取单元,从图像中提取每个特征点处的数量;特征量匹配单元, 输入图像,其中通过提取单元提取量;不变特征量计算单元,其通过匹配单元计算预定数量的图像中的匹配量的平均值作为不变特征量;距离信息获取单元,其计算距离 基于在获取图像时的机器人的位置对应于每个不变特征量的信息,以及生成本地计量图作为混合图的地图生成单元。