Adaptive motion generation using imitation learning and highly compliant end effector for autonomous cleaning

G. A. Garcia Ricardez*, N. Koganti, P. C. Yang, S. Okada, P. M. Uriguen Eljuri, A. Yasuda, L. El Hafi, M. Yamamoto, J. Takamatsu, T. Ogasawara

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Recent demographic trends in super aging societies, such as Japan, is leading to severe worker shortage. Service robots can play a promising role to augment human workers for performing various household and assistive tasks. Toilet cleanup is one such challenging task that involves performing complaint motion planning in a constrained toilet setting. In this study, we propose an end-to-end robotic framework to perform various tasks related to toilet cleanup. Our key contributions include the design of a complaint and multipurpose end-effector, an adaptive motion generation algorithm, and an autonomous mobile manipulator capable of garbage detection, garbage disposal and liquid removal. We evaluate the performance of our framework with the competition setting used for toilet cleanup in the Future Convenience Store Challenge at the World Robot Summit 2018. We demonstrate that our proposed framework is capable of successfully completing all the tasks of the competition within the time limit.

Original languageEnglish
Pages (from-to)189-201
Number of pages13
JournalAdvanced Robotics
Volume34
Issue number3-4
DOIs
Publication statusPublished - 2020 Feb 16
Externally publishedYes

Keywords

  • adaptive motion generation
  • complaint end-effector
  • Future Convenience Store Challenge
  • garbage disposal
  • Toilet cleanup
  • World Robot Summit

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Science Applications

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