Multi-vision based both-arm robot hand-eye coordination method
A robot hand and multi-eye vision technology, applied in the field of robot vision, can solve problems such as the failure of the robot arm to grasp, the blind spot of the target object, the inability of the binocular camera to capture the target object at the same time, etc., so as to improve the probability of successfully capturing the target and improve the Accuracy, the effect of solving visual blind spots
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Embodiment 1
[0072] like Figure 4 As shown, a stereo vision model of two cameras with random positions is established, and two single cameras are randomly placed. In the traditional binocular system, the world coordinate system is set on a camera coordinate system to reduce the amount of calculation, but in the present invention, the camera that collects the image is unknown, so it is meaningless to set the origin of the world coordinate system on the camera coordinate system. , so the present invention takes the end of any robot arm as the origin to establish the world coordinate system.
[0073] The two images with the target feature used in this embodiment are captured by two cameras on the same manipulator, and the end of the manipulator is used as the origin of the world coordinate system, then according to the target object p, the image coordinate system of the two images is The coordinates (x, y) in , respectively get the coordinates (x, y) of the target object p in the two camera...
Embodiment 2
[0077] The two images with target features used in this embodiment are captured by cameras on two robotic arms respectively, and one of the images is captured by a camera on a robotic arm that establishes a world coordinate system, then the target object is in the camera coordinate system. The relationship between the coordinates in and the coordinate system in the world coordinate system is:
[0078]
[0079] Another picture comes from another robotic arm, at this time the matrix M=M 2 T 1 T 2 T 3 , where T 1 represents the transformation matrix from the end of the other robotic arm to the base, T 2 represents the transformation matrix between the two manipulator bases, T 3 Represents the transformation matrix from the base of the manipulator that establishes the world coordinate system to the end of the manipulator, M 2 Represents the transfer matrix from the camera on the robotic arm that establishes the world coordinate system to the end of the robotic arm, then t...
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