DocumentCode :
2020694
Title :
On specifying and performing visual tasks with qualitative object models
Author :
Hager, Gregory D. ; Dodds, Zachary
Author_Institution :
Dept. of Comput. Sci., Johns Hopkins Univ., Baltimore, MD, USA
Volume :
1
fYear :
2000
fDate :
2000
Firstpage :
636
Abstract :
Vision-based control has aimed to develop general-purpose, high accuracy systems for manipulating objects. While much of the scientific and technological infrastructure needed to accomplish this aim is now in place, several stumbling blocks still remain. One continuing issue is accuracy, and its relationship to system calibration. We describe a generative task structure for vision-based control of motion that admits a simple, geometric approach to task specification. At the same time, this approach allows one to state precisely what types of miscalibration lead to errors in task performance. A second hurdle has been the programmability of hand-eye systems. However, we argue that a structured object representation sufficient for flexible hand-eye coordination is a possibility. The result is a high-level, object-centered language for expressing hand-eye tasks
Keywords :
calibration; motion control; object recognition; optical tracking; robot programming; robot vision; hand-eye systems; motion control; object recognition; programmability; robot programming; system calibration; vision-based control; visual tracking; Artificial intelligence; Calibration; Computer science; Control systems; Educational institutions; Feedback control; Focusing; Libraries; Robot kinematics; Robot vision systems;
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.2000.844124
Filename :
844124
Link To Document :
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