Abstract
Random bin picking is one of the most challenging industrial robotics applications available. It constitutes a complicated interaction between the vision system, robot, and control system. For a packaging operation requiring a pick-and-place task, the robot system utilized should be able to perform certain functions for recognizing the applicable target object from randomized objects in a bin. In this paper, we introduce a robotic vision system for bin picking using industrial dual-arm robots. The proposed system recognizes the best object from randomized target candidates based on stereo vision, and estimates the position and orientation of the object. It then sends the result to the robot control system. The system was developed for use in the packaging process of cell phone accessories using dual-arm robots.
Highlights
Automation has been most successfully used in manufacturing systems, and can be an effective solution in part-packaging processes at industrial sites because such processes are simple and repetitive tasks [1]
Rodrigues et al [3] build a multi-light imaging system and develop a data-driven method for pose estimation using random ferns to map the patch appearance into pose hypotheses votes
It recognizes the best picking object from randomized target objects based on stereo vision, and sends the position and orientation information of the object to the robot control system
Summary
Automation has been most successfully used in manufacturing systems, and can be an effective solution in part-packaging processes at industrial sites because such processes are simple and repetitive tasks [1]. Rahardja and Kosaka [2] propose a vision-based bin picking architecture that utilizes simple visual cues as triggers toward recognition and pose estimation of target objects. We present a robotic vision based bin picking system for industrial robotics applications. The proposed system is used in the packaging process for cell phone accessories using dual-arm robots It recognizes the best picking object from randomized target objects based on stereo vision, and sends the position and orientation information of the object to the robot control system. The developed robotic vision system performs detection and recognition functions of the target object in multiple bins and provides the information for sequential executions of the pick-and-place operations to the robot control system. One is a case of an overexposure of lighting, and the other is an appropriate illumination using a lighting device with a polarizing filter
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