Human-like motion planning of robotic arms based on human arm motion patterns

Jing Zhao, Chengyun Wang, Biyun Xie

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Robots with human-like appearances and structures are usually well accepted in the human-robot interaction. However, compared with human-like appearances and structures, the human-like motion plays a much more critical role in improving the efficiency and safety of the human-robot interaction. This paper develops a human-like motion planner based on human arm motion patterns (HAMPs) to fulfill the human-robot object handover tasks. First, a handover task is divided into two sub-tasks, that is, pick-up and delivery, and HAMPs are extracted for these two sub-tasks separately. The resulting HAMPs are analyzed, and a method is proposed to select HAMPs that can represent the characteristics of the human arm motion. Then the factors affecting the duration of the movement primitives are analyzed, and the relationship between the duration of the movement primitives and these factors is determined. Based on the selected HAMP and the computed duration of the movement primitives, a human-like motion planning framework is developed to generate the human-like motion for the robotic arms. Finally, this motion planner is verified by the human-robot handover experiments using a KUKA IIWA robot. It shows that the resulting trajectories can correctly reflect the relative relationship between the joints in the human arm motion and are very close to the recorded human arm trajectories. Furthermore, the proposed motion planning method is compared with the motion planning method based on minimum total potential energy. The results show that the proposed method can generate more human-like motion.

Original languageEnglish
Pages (from-to)259-276
Number of pages18
JournalRobotica
Volume41
Issue number1
DOIs
StatePublished - Jan 27 2023

Bibliographical note

Publisher Copyright:
© 2022 The Author(s).

Keywords

  • Rapid upper limb assessment (RULA)
  • human arm motion patter
  • human-robot interaction
  • movement primitive
  • robot human-like motion planning

ASJC Scopus subject areas

  • Software
  • Mechanical Engineering
  • Control and Optimization
  • Artificial Intelligence
  • Rehabilitation
  • Control and Systems Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Computational Mechanics
  • General Mathematics
  • Modeling and Simulation

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