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An integrated object representation for recognition and grasping

E. Kefalea, Eric Maël, Rolf P. Würtz

发表年份
2003
引用次数
8

摘要

As a step towards systems that can acquire knowledge automatically, we have designed a system that can learn new objects with a minimum of user interaction and implemented it on our robot platform GripSee (M. Becker et al., 1999). A novel object is placed into the robot's gripper in order to define a default orientation and a default grip. The robot then places the object on a turning table and builds up a visual representation that consists of a collection of graphs, labeled with multiscale edges. A user interface that can correct errors in the representation is also part of the system. The visual representation is complemented by a grip library, which contains possible ways of grasping and manipulating the object in a robust manner. We regard this procedure as an example of human assisted learning.

关键词

Computer scienceRepresentation (politics)Artificial intelligenceObject (grammar)Table (database)RobotOrientation (vector space)Computer visionHuman–computer interactionInterface (matter)

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