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OBJECT-TO-ROBOT POSE ESTIMATION FROM A SINGLE RGB IMAGE

机译:单个RGB图像的对象到机器人姿势估计

摘要

Pose estimation generally refers to a computer vision technique that determines the pose of some object, usually with respect to a particular camera. Pose estimation has many applications, but is particularly useful in the context of robotic manipulation systems. To date, robotic manipulation systems have required a camera to be installed on the robot itself (i.e. a camera-in-hand) for capturing images of the object and/or a camera external to the robot for capturing images of the object. Unfortunately, the camera-in-hand has a limited field of view for capturing objects, whereas the external camera, which may have a greater field of view, requires costly calibration each time the camera is even slightly moved. Similar issues apply when estimating the pose of any object with respect to another object (i.e. which may be moving or not). The present disclosure avoids these issues and provides object-to-object pose estimation from a single image.
机译:姿势估计通常是指一种计算机视觉技术,该技术通常确定特定摄像机相对于某些物体的姿态。姿势估计有许多应用,但是在机器人操纵系统的环境中特别有用。迄今为止,机器人操纵系统已经要求将摄像机安装在机器人本身上(即,手持摄像机)以捕获对象的图像和/或在机器人外部安装摄像机以捕获对象的图像。不幸的是,手持摄像机的视野有限,无法捕获物体,而外接摄像机可能具有较大的视野,每次摄像机稍微移动时,都需要进行昂贵的校准。当估计任何物体相对于另一物体(即可能移动或不移动)的姿态时,也会遇到类似的问题。本公开避免了这些问题,并且从单个图像提供了对象到对象的姿势估计。

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