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Demonstrating Naviarm: Augmenting the Learning of Motor Skills using a Backpack-type Robotic Arm System

Published: 11 March 2019 Publication History

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 prerecords 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 our demonstration, the user will experience the recording of arm movement with backpack-type robotic arm. Then, the recorded movement will replayed and the user can experience the haptic feedback.

References

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National Institution of Technology and Evaluation. 2013. Human Characteristics Database. (2013). http://www.tech.nite.go.jp/human/
[2]
Research Institute of Human Engineering for Quality Life. 2008. Japanese Anthropometric Database 2004-2006. (2008). https://www.hql.jp/database/cat/size/size2004
[3]
MHD Yamen Saraiji, Tomoya Sasaki, Kai Kunze, Kouta Minamizawa, and Masahiko Inami. 2018. MetaArms: Body Remapping Using Feet-Controlled Artificial Arms. In The 31st Annual ACM Symposium on User Interface Software and Technology. ACM, 65--74.
[4]
Misako Sawada, Shiro Mori, and Motonobu Ishii. 2002. Effect of metaphorical verbal instruction on modeling of sequential dance skills by young children. Perceptual and motor skills 95, 3_suppl (2002), 1097--1105.

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  1. Demonstrating Naviarm: Augmenting the Learning of Motor Skills using a Backpack-type Robotic Arm System

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      cover image ACM Other conferences
      AH2019: Proceedings of the 10th Augmented Human International Conference 2019
      March 2019
      301 pages
      ISBN:9781450365475
      DOI:10.1145/3311823
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 11 March 2019

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      Author Tags

      1. Augmented learning
      2. Haptics
      3. Motor Learning
      4. Robotics
      5. Wearable Device

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      • Demonstration
      • Research
      • Refereed limited

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      AH2019

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      AH2019 Paper Acceptance Rate 26 of 53 submissions, 49%;
      Overall Acceptance Rate 121 of 306 submissions, 40%

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