Minimal Grasper: A Practical Robotic Grasper With Robust Performance for Pick-and-Place Tasks
JingFu Jin, Shang Li Yuen, Young Ho Lee, Changhyun Jun, Youngji Brigid Kim, Sungon Lee, Bum-Jae You, Nakju Lett Doh
- 发表年份
- 2012
- 引用次数
- 17
摘要
In this paper, a flexible enveloping grasper is proposed for pick-and-place tasks with low manipulation and task planning complexity for practical applications. The proposed grasper has two main characteristics: self-adaptivity and flexibility. Self-adaptivity means that the proposed grasper can grip an object in a self-adaptive way such that various process complexities (e.g., sensing, force control, and sensor-motor coordination) are significantly reduced. By flexibility, we mean that, by using a flexible material, a stable grip can be implemented to cause increased friction between the grasper and the target object as a result of increased contact area. These two properties help the proposed grasper to minimize internal forces in a passive manner and to achieve successful force distribution with self-adaptivity when performing enveloping grasping. Three sets of experiments were performed with an average success rate of 93.2% in pick-and-place tasks.
关键词
相关论文
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