Cost Functions based Dynamic Optimization for Robot Action Planning

Weitian Wang, Yi Chen, Zachary Max Diekel, Yunyi Jia

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

2 Scopus citations

Abstract

Human-robot collaboration provides a great solution to the complex hybrid assembly tasks of intelligent manufacturing. In order to augment and guarantee the task quality in the human-robot collaboration process, the collaboration efficiency, including time consumption and human efforts, should be considered in the robot action planning. In this study, we propose a novel and practical approach using cost functions for the robot to plan actions in human-robot collaboration to address this challenge. By this approach, the robot action planning can be dynamically optimized to determine assisted assembly steps in the human-robot co-assembly task. A preliminary experiment is conducted to evaluate the proposed approach. Experimental results suggest that the proposed approach successfully generates the optimal actions for the robot to improve the task efficiency in human-robot collaboration.

Original languageEnglish
Title of host publicationHRI 2018 - Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction
PublisherIEEE Computer Society
Pages277-278
Number of pages2
ISBN (Electronic)9781450356152
DOIs
StatePublished - 1 Mar 2018
Event13th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2018 - Chicago, United States
Duration: 5 Mar 20188 Mar 2018

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)2167-2148

Conference

Conference13th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2018
Country/TerritoryUnited States
CityChicago
Period5/03/188/03/18

Keywords

  • collaborative assembly
  • cost functions
  • human-robot collaboration
  • robot action planning

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