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