De-electroadhesion of Flexible and Lightweight Materials: An Experimental Study
Chongjing Cao, Xing Gao, Jianglong Guo, Andrew T. Conn
- Year
- 2019
- Citations
- 14
- Access
- Open access
Abstract
Electroadhesion (EA) is an emerging prehension method with wide application in robotics, including object handling, component assembly, and robotic locomotion. A major challenge with EA is the development of novel solutions for speeding up the release process, where residual charges inhibit release. In this work, a comprehensive study on the effects of EA base substrate and object material types on de-electroadhesion time is presented. Experimental results show that the de-electroadhesion speed is highly dependent on the base substrate and object material type. There is a strong inverse correlation between dielectric constant and de-electroadhesion rate, while a higher molecular weight demonstrates slower dielectric relaxation and hence release time. These findings will enable the design of cost-effective EA-based robotic end effectors with rapid release capabilities. EA grippers with quicker de-adhesion abilities could significantly improve the overall throughput of assembly lines where material pick-and-place tasks are involved. In addition, more efficient and faster locomotion speeds could be achieved for crawling or climbing robots where EA is employed as their active adhesion and de-adhesion feet.
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