Development and characterization of a multi-camera 2D-vision system for enhanced performance of a drink serving robotic cell

A 2D-vision system is integrated into a drink-serving robotic cell, to enhance its flexibility. Two videocameras are used in a hybrid configuration scheme. The former is rigidly mounted on the robot end effector, the latter is fixed to the workplace. The robot cell is based on two Denso robots that interoperate to simulate real human tasks. Blob analysis, template matching and edge detection algorithms cooperate with motion procedures for fast object recognition and flexible adaptation to the environment. The paper details the system workflow, with particular emphasis to the vision procedures. The experimental results show their performance in terms of flexibility and robustness against defocusing, lighting conditions and noise.

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