DocumentCode :
2033677
Title :
Self-learning vision-guided robots for searching and grasping objects
Author :
Nguyen, Minh-Chid ; Graefe, Volker
Author_Institution :
Inst. of Meas. Sci., Bundeswehr Univ., Munich, Germany
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
1633
Abstract :
An approach to control vision-guided robots is introduced. It allows searching and grasping differently shaped objects that may be located anywhere in the robot´s work space, even not visible in the initial fields of view of cameras. It eliminates the need for a calibration of the robot and of the vision system, it uses no world coordinates and no inverse perspective or kinematic transformations, and it comprises an automatic adaptation to changing parameters. The approach has been implemented on a calibration-free vision-guided manipulator with five degrees of freedom (DOF) and was evaluated in real-word experiments
Keywords :
feature extraction; learning (artificial intelligence); manipulators; position control; robot vision; stereo image processing; automatic adaptation; calibration-free vision-guided manipulator; five degrees of freedom manipulator; grasping; searching; self-learning vision-guided robots; Calibration; Cameras; Grippers; Jacobian matrices; Orbital robotics; Robot control; Robot kinematics; Robot sensing systems; Robot vision systems; Robotics and automation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on
Conference_Location :
San Francisco, CA
ISSN :
1050-4729
Print_ISBN :
0-7803-5886-4
Type :
conf
DOI :
10.1109/ROBOT.2000.844830
Filename :
844830
Link To Document :
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