Feature-based camera-guided grasping by an eye-in-hand robot
Anneliese Schrott
- Year
- 2003
- Citations
- 20
Abstract
The author proposes a method of feature-based camera-guided grasping of a known object by splitting up the 3D movement in several successive 1D or 2D movements. Object recognition was achieved by extracting the 3D features of the object from image sequences while a camera mounted on a robots hand was moving toward the object. After the recognition of the object, the camera approached the object by several camera-guided steps: motion in the xy-plane, rotations around the z-axis, and movements along the z-axis. These movements were controlled by data which were derived from the image features. Finally, the gripper had to do a fine motion to reach the correct position for the grasping of the object.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002