Cognitive gripping with flexible graphene printed multi-sensor array
Tania Mukherjee, Dipti Gupta
- Year
- 2023
- Citations
- 4
- Access
- Open access
Abstract
Abstract Robotics for task simplification of domestic, household, workplace and other assistive activities require efficient robots with decision-making capabilities. Here we report a fully printed graphene-based capacitive multi-sensor array (CAPSENSAR) employed in a cognitive robotic gripper (COGBOT) for decision-making operations. The CAPSENSAR created a contactless capacitive impression of the gripped object surface to determine the optimum gripping pressure. The controlling unit of the COGBOT was associated with an algorithm to address potential breakage. If slippage was detected via the array, the grip pressure was revised to reduce the possibility for damage. This facilitated slippage-free and damage-resistant gripping of the target objects without user interference. Array fabrication was straightforward using a customizable electrode design with cost-effective and biocompatible materials.
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