Modeling and human performance in manipulating parallel flexible objects

Mikhail Svinin', Igor Goncharenko, Victor Kryssanov, Motoji Yamamoto

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter presents an analysis of human-like reaching movements in manipulation of parallel flexible objects. To predict a trajectory of the human hand, a minimum hand-jerk model and a minimum hand-force-change model based on the minimization of the integral of, respectively, squared hand jerk and squared time derivative of the hand force over the movement duration are established. It is shown that within these models, the optimal hand trajectory is composed of a fifth-order polynomial and trigonometric terms depending on the natural frequencies of the system and movement time. To estimate the mass of the hand featured in the minimum hand-force-change model, a method based on following a periodic force input is proposed. A virtual reality-based experimental setup with a haptic simulator is designed, and the predictions by the minimum hand-jerk and force-change models are verified against experimental data. The theoretical predictions match the collected data with a reasonable accuracy. The experimental results show the applicability of the two considered models for the generation of human-like reaching movements in dynamic environments.

Original languageEnglish
Title of host publicationHuman Inspired Dexterity in Robotic Manipulation
PublisherElsevier
Pages61-83
Number of pages23
ISBN (Electronic)9780128133965
ISBN (Print)9780128133859
DOIs
Publication statusPublished - Jun 29 2018

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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