Human Modeling for Bio-Inspired Robotics

Mechanical Engineering in Assistive Technologies

Jun Ueda, Yuichi Kurita

• Publisher: Academic Press
• Year: 2016
• ISBN:
  9780128031520
• Topic: Technology & Engineering
• Subtopic: Biomedical Science
• Index: Technology & Engineering

Human Modelling for Bio-inspired Robotics: Mechanical Engineering in Assistive Technologies presents the most cutting-edge research outcomes in the area of mechanical and control aspects of human functions for macro-scale (human size) applications. Intended to provide researchers both in academia and industry with key content on which to base their developments, this book is organized and written by senior experts in their fields.

Human Modeling for Bio-Inspired Robotics: Mechanical Engineering in Assistive Technologies offers a system-level investigation into human mechanisms that inspire the development of assistive technologies and humanoid robotics, including topics in modelling of anatomical, musculoskeletal, neural and cognitive systems, as well as motor skills, adaptation and integration. Each chapter is written by a subject expert and discusses its background, research challenges, key outcomes, application, and future trends.

This book will be especially useful for academic and industry researchers in this exciting field, as well as graduate-level students to bring them up to speed with the latest technology in mechanical design and control aspects of the area. Previous knowledge of the fundamentals of kinematics, dynamics, control, and signal processing is assumed.

• Presents the most recent research outcomes in the area of mechanical and control aspects of human functions for macro-scale (human size) applications
• Covers background information and fundamental concepts of human modelling
• Includes modelling of anatomical, musculoskeletal, neural and cognitive systems, as well as motor skills, adaptation, integration, and safety issues
• Assumes previous knowledge of the fundamentals of kinematics, dynamics, control, and signal processing

Part I

Modeling of Human Musculoskeletal System/Computational Analysis of Human Movements and Their Applications

Chapter One

Implementation of Human-Like Joint Stiffness in Robotics Hands for Improved Manipulation

A. Deshpande; T. Niehues; P. Rao University of Texas, Austin, TX, United States

Abstract

Humans exploit the inherent biomechanical compliance in their fingers to achieve stability and dexterity during many manipulation tasks. The compliance is a result of muscles, tendons (series compliance), and flexible joints (parallel compliance). While the effects of series compliance have been studied in many robotic systems, research on the effects of joint compliance arranged in parallel with the actuators is limited.

In this chapter we first present an approach for modeling the passive stiffness at the human metacarpophalangeal joint, and the individual contributions from the elasticity of muscle-tendon units (MTUs) and capsule ligament complex (CLC). Toward this goal, we conducted experiments with 10 human subjects and collected joint angle and finger tip force data. The total passive moment and joint angle data were fitted with a double exponential model, and the passive moments due to the MTUs were determined by developing subject-specific models of the passive force length relationships. Our results show that for all the subjects, the work done by the passive moments from the MTUs is less than 50% of total work done, and the CLC provides dominant contributions to the joint stiffness throughout the flexion-extension range of motion.

We then demonstrate, through mathematical modeling, that introducing parallel compliance improves stability and robustness in the presence of time delay in a generic robotic joint. We also provide guidelines to balance the benefits of added stability with increased actuator load when implementing parallel compliance in robotic joints. We designed two 2-DOF tendon-driven fingers with parallel compliance, and developed an impedance control law for object manipulation with the fingers. Experimental results demonstrate the advantages of introducing parallel compliance in robotic hands during dexterous manipulation tasks, specifically in achieving smoother trajectory tracking, improved stability, and robustness to impacts.

Keywords

Human hand; Joint stiffness; Manipulation; Joint compliance; Robotic joint; Series, Parallel compliance

1 Introduction

In the past two decades, a number of robotic hands have been designed with compliance with the goal of improving interaction stability, robustness, and manipulation abilities. In the human hand, the intrinsic, passive joint stiffness of the fingers critically affects the hand functions and joint stability [1–3]. Because of its prominent role in many hand functions, a number of studies have focused on investigating the joint stiffness of the index finger metacarpophalangeal (MCP) joint [2, 4–7]. The muscle-tendon units (MTUs) contribute to the passive MCP joint stiffness by generating resistive forces when stretched [2, 3]. In addition to the MTUs, the capsule-ligament complex (CLC) at the joint provides resistance, especially to prevent joint instability. We carry out a quantitative analysis to determine the relative contributions of MTUs and CLC to the passive joint stiffness, in various finger configurations. It has been established through a number of previous studies that the resistive moment generated at the MCP joint due to the joint stiffness has a double exponential dependency on the joint angle [4, 5]. A number of previous studies assume, either explicitly or implicitly, that this joint stiffness is strictly due to the passive forces from the stretching of muscles and tendons, and that the effect of CLC can be ignored [7, 8].

Inspired by the dominant role of joint compliance in the human hands, we explore the role of mechanical springs added in parallel to the joint actuators (parallel compliance) in robotic hands. While the series compliance, introduced through series elastic actuators (SEA), has been studied extensively [9] an...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Contributors
• Motivation
• About This Book
• Part I: Modeling of Human Musculoskeletal System/Computational Analysis of Human Movements and Their Applications
• Part II: Modeling of Human Cognitive/Muscular Skills and Their Applications
• Index