MANIPULATION
Manipulation of deformable linear objects using knot invariants to classify the object condition based on image sensor information
Takayuki Matsuno, Daichi TAMAKI, Fumihito Arai, Toshio Fukuda
- 发表年份
- 2006
- 引用次数
- 46
摘要
Using a topological model and knot theory, we propose a method for describing the condition of a rope. We also propose a recognition method based on the image information obtained from the charge-coupled device cameras to obtain the structure of the rope when manipulated by a robot. This method will help solve the difficulties of robots manipulating deformable objects by providing a theoretical framework of error recovery for deformable object manipulation. We confirm the effectiveness of the methods through experiments
关键词
RopeKnot (papermaking)Computer visionArtificial intelligenceRobotComputer scienceObject (grammar)Image (mathematics)AlgorithmEngineering
相关论文
OTHER
📊 26,957 引用
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 引用
Artificial intelligence: a modern approach
1995
OTHER
📊 18,993 引用
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
SWARM
📊 14,853 引用
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002