Abstract: A system and method facilitate machine-vision, for example three-dimensional pose estimation for target objects, using one or more images sensors to acquire images of the target object at one or more positions, and to identify features of the target object in the resulting images. A set of equations is set up exploiting invariant physical relationships between features such as constancy of distances, angles, and areas or volumes enclosed by or between features. The set of equations may be solved to estimate a 3D pose. The number of positions may be determined based on the number of image sensors, number of features identified, and/or number of known physical relationships between less than all features. Knowledge of physical relationships between image sensors and/or between features and image sensors may be employed. A robot path may be transformed based on the pose, to align the path with the target object.

Abstract: A system and method facilitate machine-vision, for example three-dimensional pose estimation for target objects, using one or more images sensors to acquire images of the target object at one or more positions, and to identify features of the target object in the resulting images. A set of equations is set up exploiting invariant physical relationships between features such as constancy of distances, angles, and areas or volumes enclosed by or between features. The set of equations may be solved to estimate a 3D pose. The number of positions may be determined based on the number of image sensors, number of features identified, and/or number of known physical relationships between less than all features. Knowledge of physical relationships between image sensors and/or between features and image sensors may be employed. A robot path may be transformed based on the pose, to align the path with the target object.

Abstract: A method of three-dimensional handling of an object by a robot uses a tool and one camera mounted on the robot and at least six target features which are normal features of the object are selected on the object. The features are used to train the robot in the frame of reference of the object so that when the same object is subsequently located, the robot's path of operation can be quickly transformed into the frame of reference of the object.