Action Planning for Packing Long Linear Elastic Objects Into Compact Boxes With Bimanual Robotic Manipulation

Wanyu Ma, Bin Zhang, Lijun Han, Shengzeng Huo, Hesheng Wang, David Navarro-Alarcon

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

In this article, we propose a new action planning approach to automatically pack long linear elastic objects into common-size boxes with a bimanual robotic system. For that, we developed a hybrid geometric model to handle large-scale occlusions combining an online vision-based method and an offline reference template. Then, a reference point generator is introduced to automatically plan the reference poses for the predesigned action primitives. Finally, an action planner integrates these components enabling the execution of high-level behaviors and the accomplishment of packing manipulation tasks. To validate the proposed approach, we conducted a detailed experimental study with multiple types and lengths of objects and packing boxes.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalIEEE/ASME Transactions on Mechatronics
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • 3-D point clouds
  • action planning
  • automatic packing
  • elastic objects
  • robotic manipulation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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