DocumentCode :
137649
Title :
Vision guided robotic block stacking
Author :
Macias, Nathanael ; Wen, J.
Author_Institution :
Appl. Phys. Lab., Laurel, MD, USA
fYear :
2014
fDate :
14-18 Sept. 2014
Firstpage :
779
Lastpage :
784
Abstract :
Industrial robots are precise and efficient at performing repetitive tasks. However, robots lack the ability to recognize and manipulate objects. They rely on human operators to translate the desired task into a set of operations that it can perform. The research area of bin-picking aims to provide robots with the ability to manipulate randomly ordered objects in unstructured environments. This research focuses on developing a robust vision guided robotic block pick-up and stacking system. We use binary markers to aid in block identification and localization, a custom 3D-printed gripper for robust grasping, and planning algorithms to determine the grasp sequence. By integrating a low-cost webcam with an industrial robot, our system is able to observe the block locations in a random pile, determine the appropriate response necessary to grasp, and sequence to remove blocks from a pile.
Keywords :
bin packing; grippers; industrial manipulators; object recognition; path planning; robot vision; bin-picking; binary markers; block identification; block localization; custom 3D-printed gripper; grasp sequence determination; industrial robots; low-cost webcam; object recognition; planning algorithms; random pile; randomly ordered object manipulation; robust grasping; robust vision guided robotic block pick-up and stacking system; unstructured environments; Cameras; Grippers; Robot vision systems; Service robots;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on
Conference_Location :
Chicago, IL
Type :
conf
DOI :
10.1109/IROS.2014.6942647
Filename :
6942647
Link To Document :
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