Underactuation Design for Tendon-driven Hands via Optimization of Mechanically Realizable Manifolds in Posture and Torque Spaces

TL;DR

This paper introduces an optimization method for designing underactuated robotic hands that shape mechanically realizable grasp synergies to match desired grasp patterns, ensuring physical implementability and effective grasping.

Contribution

It proposes a novel approach to optimize underactuated hand design parameters for shaping grasp synergies as low-dimensional manifolds in posture and torque spaces.

Findings

Optimized hand designs successfully achieve desired grasp postures.

Designed synergies enable the hand to reach and maintain stable grasps.

Method demonstrates practical effectiveness on real-world examples.

Abstract

Grasp synergies represent a useful idea to reduce grasping complexity without compromising versatility. Synergies describe coordination patterns between joints, either in terms of position (joint angles) or effort (joint torques). In both of these cases, a grasp synergy can be represented as a low-dimensional manifold lying in the high-dimensional joint posture or torque space. In this paper, we use the term \textit{Mechanically Realizable Manifolds} to refer to the subset of such manifolds (in either posture or torque space) that can be achieved via mechanical coupling of the joints in underactuated hands. We present a method to optimize the design parameters of an underactuated hand in order to shape the Mechanically Realizable Manifolds to fit a pre-defined set of desired grasps. Our method guarantees that the resulting synergies can be physically implemented in an underactuated hand, and will enable the resulting hand to both reach the desired grasp postures and achieve quasistatic equilibrium while loading the grasps. We demonstrate this method on three concrete design examples motivated by a real use case, and evaluate and compare their performance in practice.