Simultaneous dual-arm motion planning for minimizing operation time

Jun Kurosu, Ayanori Yorozu, Masaki Takahashi

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Dual-arm robots are expected to perform work in a dynamic environment. One of the most basic tasks that a dual-arm robot does is pick-and-place work. However, this work is more complicated when there are several objects in the robot's workspace. Additionally, it is likely to take a long time to finish the work as the number of objects increases. Therefore, we propose a method using a combination of two approaches to achieve efficient pick-and-place performance by a dual-arm robot to minimize its operation time. First, we use mixed integer linear programming (MILP) for the pick-and-place work to determine which arm should move an object and in which order these objects should be moved while considering the dual-arm robot's operation range. Second, we plan the path using the rapidly exploring random tree so that the arms do not collide, enabling the robot to perform efficient pick-and-place work based on the MILP planning solution. The effectiveness of the proposed method is confirmed by simulations and experiments using an actual dual-arm robot.

Original languageEnglish
Article number1210
JournalApplied Sciences (Switzerland)
Volume7
Issue number12
DOIs
Publication statusPublished - 2017 Nov 23

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robot arms
Motion planning
planning
Robots
linear programming
robots
integers
Linear programming
Planning
simulation

Keywords

  • Dual-arm robot
  • Manipulation
  • Motion planning
  • Pick-and-place

ASJC Scopus subject areas

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

Cite this

Simultaneous dual-arm motion planning for minimizing operation time. / Kurosu, Jun; Yorozu, Ayanori; Takahashi, Masaki.

In: Applied Sciences (Switzerland), Vol. 7, No. 12, 1210, 23.11.2017.

Research output: Contribution to journalArticle

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