Finger trajectory generation for planar dexterous micro-manipulation

Abstract

Dexterous micro-manipulation is a promising way to perform complex manipulation in micro-scale. Current dexterous micro-handling solutions are often limited to small amplitude rotations (around 90°) and to simple shaped objects (such as squares). Our approach consists in developing in-hand micro-manipulation techniques using dexterous micro-hands, taking advantage of adhesion forces, to manipulate arbitrary shaped objects. This paper focuses on the trajectory generation of a dexterous micro-hand to achieve automated repositioning. The statistical results on the generated trajectories show that the adhesion forces in micro-scale can be exploited to enhance micro-manipulation.