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Motion Planning for Human-Robot Collaboration Using an Objective-Switching Strategy

  • Akira Kanazawa*
  • , Jun Kinugawa
  • , Kazuhiro Kosuge
  • *Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

Motion planning of collaborative robots is often required to simultaneously satisfy the contradictory objectives of reliably avoiding human workers and safely approaching them. In this article, we propose a new strategy that adaptively selects one of two objective functions based on the current operational region of the robot; the objective function for avoiding the worker with a distance larger than the safe distance, and the objective function for approaching the worker with a speed limitation for human safety. This strategy improves the worker safety while limiting the negative impact of the speed limit on time efficiency. The chattering related to the switching between the two objectives is solved using a continuous approximation of the switching based on uncertainties of the predicted worker's motion. We implement the proposed motion planning with the objective-switching strategy into a collaborative assembly system to deal with the worker moving with high irregularities. We experimentally evaluate the effectiveness of the proposed motion planning from the safety and efficiency points of view.

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Original languageEnglish
Pages (from-to)590-600
Number of pages11
JournalIEEE Transactions on Human-Machine Systems
Volume51
Issue number6
Online published11 Oct 2021
DOIs
Publication statusPublished - Dec 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Research Keywords

  • Cognitive human-robot interaction
  • collaborative robot
  • learning and adaptive systems
  • motion planning

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