Hand-Eye Coordination of a Robotic Arm Using a Stereo Camera
Abstract
This work presents the results obtained after implementing a computer vision algorithm developed in Python to estimate the position of an object through visual information from a stereo camera. The object’s position estimation is utilized by the controller of a robotic arm to position it for grasping the object. However, the robotic arm does not always reach the expected point accurately. Consequently, this process was complemented with a position correction algorithm based on the Gradient Descent optimization algorithm and the hand-eye coordination process performed by humans.The position values are sent via wifi using the TCP/IP protocol through sockets to the robotic arm controller. Experimental results demonstrate that, with higher camera image resolution, the object’s position estimation improves. Overall, with the implemented correction algorithm, the distance between the robot’s final position and the object’s position does not exceed 10 mm.
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References
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