MANIPULATION
Robust and fast generation of top and side grasps for unknown objects
Brice Denoun, Beatriz León, Claudio Zito, Rustam Stolkin, Lorenzo Jamone, Miles Hansard
- Year
- 2019
- Citations
- 2
- Access
- Open access
Abstract
In this work, we present a geometry-based grasping algorithm that is capable of efficiently generating both top and side grasps for unknown objects, using a single view RGB-D camera, and of selecting the most promising one. We demonstrate the effectiveness of our approach on a picking scenario on a real robot platform. Our approach has shown to be more reliable than another recent geometry-based method considered as baseline [7] in terms of grasp stability, by increasing the successful grasp attempts by a factor of six.
Keywords
GRASPComputer scienceComputer visionArtificial intelligenceBaseline (sea)RGB color modelRobotStability (learning theory)RoboticsMachine learning
Related papers
OTHER
📊 26,957 cites
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 cites
Artificial intelligence: a modern approach
1995
OTHER
📊 18,993 cites
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
SWARM
📊 14,853 cites
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002