Robot Motion Planning with Human-Like Motion Patterns based on Human Arm Movement Primitive Chains

Shiqiu Gong, Jing Zhao, Biyun Xie

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

A novel motion planning method is proposed to generate human-like motion for anthropomorphic robot arms. Its highlight is to consider the robot arm to be human-like not only in its configuration but also in its motion patterns. To achieve this, the intrinsic mechanisms of human arm motion generation are transferred to robot motion planning. First, human arm motion is modeled using human arm motion primitives. The mechanisms of human arm motion generation are dissected from a large number of motion samples, reflected in the types, sequencing and quantification rules/laws of the primitives. Next, the human arm motion patterns are studied based on primitive chains. Finally, a new motion planning method is built that autonomously performs motion pattern decisions, motion time allocation, and joint trajectory generation. The proposed method is validated by a motion planning app and a robot simulation.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Robotics and Automation, ICRA 2021
Pages8373-8379
Number of pages7
ISBN (Electronic)9781728190778
DOIs
StatePublished - 2021
Event2021 IEEE International Conference on Robotics and Automation, ICRA 2021 - Xi'an, China
Duration: May 30 2021Jun 5 2021

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2021-May
ISSN (Print)1050-4729

Conference

Conference2021 IEEE International Conference on Robotics and Automation, ICRA 2021
Country/TerritoryChina
CityXi'an
Period5/30/216/5/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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