Naviarm: Augmenting the learning of motor skills using a backpack-type robotic arm system

Azumi Maekawa, Shota Takahashi, M. H.D.Yamen Saraiji, Sohei Wakisaka, Hiroyasu Iwata, Masahiko Inami

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

We present a wearable haptic assistance robotic system for augmented motor learning called Naviarm. This system comprises two robotic arms that are mounted on a user's body and are used to transfer one person's motion to another offline. Naviarm pre-records the arm motion trajectories of an expert via the mounted robotic arms and then plays back these recorded trajectories to share the expert's body motion with a beginner. The Naviarm system is an ungrounded system and provides mobility for the user to conduct a variety of motions. In this paper, we focus on the temporal aspect of motor skill and use a mime performance as a case study learning task. We verified the system effectiveness for motor learning using the conducted experiments. The results suggest that the proposed system has benefits for learning sequential skills.

Original languageEnglish
Title of host publicationProceedings of the 10th Augmented Human International Conference, AH 2019
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450365475
DOIs
Publication statusPublished - 2019 Mar 11
Event10th Augmented Human International Conference, AH 2019 - Reims, France
Duration: 2019 Mar 112019 Mar 12

Publication series

NameACM International Conference Proceeding Series

Conference

Conference10th Augmented Human International Conference, AH 2019
Country/TerritoryFrance
CityReims
Period19/3/1119/3/12

Keywords

  • Augmented learning
  • Haptics
  • Motor learning
  • Robotics
  • Wearable device

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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