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Design of a Bin-picking System for Large Objects with High Clutter and Occlusion

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Title: Design of a Bin-picking System for Large Objects with High Clutter and Occlusion
Author: Weales, David
Department: School of Engineering
Program: Engineering
Advisor: Moussa, Medhat
Abstract: This thesis presents a bin-picking system designed for large objects in bins with high clutter and occlusion. This system includes an end effector design as well as simple vision algorithms for grasping and recognition. The system overcomes vision sensor errors and uncertainty by using an innovative gripper that is both compliant and dynamic. The system was extensively tested on industrial parts in a simulated industrial environment. Results show that the system is effective at grasping objects, but has some issues recognizing and determining the pose of objects. This system was tested at a reduced speed for safety reasons, but could be capable of meeting manufacturing cycle times with some improvements.
URI: http://hdl.handle.net/10214/13007
Date: 2018-05
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