Replicating Human Anatomy with Vision Controlled Jetting -- A Pneumatic Musculoskeletal Hand and Forearm
Thomas Buchner, Stefan Weirich, Alexander M. Kübler, Wojciech Matusik, Robert K. Katzschmann
TL;DR
The paper addresses achieving human-like dexterity in a robotic hand by combining a multi-material 3D-printed, soft–rigid hybrid hand and forearm with 22 pneumatic artificial muscles actuating a tendon-driven mechanism. It leverages vision-controlled jetting to print an integrated system, including soft joint capsules and tactile sensors, and demonstrates grasping and manipulation of objects up to $272$ g with independent finger movement. Key results include range of motion metrics (Kapandji score of 6/10), a variety of grasps (power, precision, intermediate), and fingertip/grasps forces of about $1.95\,\text{N}$ and $2.97\,\text{N}$ under specific lead pressures, with maximum PAM strain of $30.1\%$ and force around $38$ N at $0.5$ MPa. The work provides a cost-effective, rapid fabrication pathway for biomimetic hands and forearms, offering practical implications for prosthetics and robot manipulation, while identifying durability and mobility challenges to be addressed in future work.
Abstract
The functional replication and actuation of complex structures inspired by nature is a longstanding goal for humanity. Creating such complex structures combining soft and rigid features and actuating them with artificial muscles would further our understanding of natural kinematic structures. We printed a biomimetic hand in a single print process comprised of a rigid skeleton, soft joint capsules, tendons, and printed touch sensors. We showed it's actuation using electric motors. In this work, we expand on this work by adding a forearm that is also closely modeled after the human anatomy and replacing the hand's motors with 22 independently controlled pneumatic artificial muscles (PAMs). Our thin, high-strain (up to 30.1%) PAMs match the performance of state-of-the-art artificial muscles at a lower cost. The system showcases human-like dexterity with independent finger movements, demonstrating successful grasping of various objects, ranging from a small, lightweight coin to a large can of 272g in weight. The performance evaluation, based on fingertip and grasping forces along with finger joint range of motion, highlights the system's potential.
