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. 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 skill.
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Azumi Maekawa, Shota Takahashi, MHD Yamen Saraiji, Sohei Wakisaka, Hiroyasu Iwata, and Masahiko Inami. 2019. Naviarm: Augmenting the Learning of Motor Skills Using a Backpack-type Robotic Arm System. In Proceedings of the 10th Augmented Human International Conference 2019 (AH2019), 38:1–38:8. https://doi.org/10.1145/3311823.3311849