Tailoring stiffness distribution of tendon-driven continuum finger from manipulation force vector

Continuum soft-robotic fingers/arms have emerged as a promising solution to realize abilities to delicately manipulate objects, conform to various shapes, and maintain cost-efficiency (i.e. fewer actuators and less computational resource). This paper introduces a novel approach to designing continuum flexible fingers by optimizing the fingers' thickness distribution to achieve specific target force vectors for specific manipulations, enabling actions like pull-in handing (retraction), push-out manipulation, secure grip, and gentle object hold. The proposed method employs a genetic algorithm to optimize the thickness distribution of the continuum finger driven by a single motor, resulting in a highly versatile and cost-effective solution. The proposed method includes physical simulations to validate the approach's effectiveness in applying desired force vectors during manipulation interactions. This work represents a significant advancement in continuum robotic systems, potentially impacting a wide range of applications in human-robot collaboration.