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논문 기본 정보

자료유형
학술대회자료
저자정보
Hee-Seung Moon (Yonsei University) Jiwon Seo (Yonsei University)
저널정보
제어로봇시스템학회 제어로봇시스템학회 국제학술대회 논문집 ICCAS 2017
발행연도
2017.10
수록면
1,276 - 1,280 (5page)

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초록· 키워드

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Haptic guidance is a promising robot-mediated training method that assists humans in completing tasks. Although several research studies showed positive effects of haptic guidance, a long-standing assumption indicated that haptic guidance impairs motor learning owing to conflicts between human and robots. In this paper, we propose localadaptive haptic guidance, which provides varied guiding forces in different localities depending on a human’s local performance. With this adaptive training method, we hypothesized that trainees learn unfamiliar tasks with less conflict and become less passive. Three types of guidance training method were compared: i) no guidance, ii) (fixed) haptic guidance, and iii) local-adaptive haptic guidance. We observed a trainee’s learning performance while the trainee repeatedly performs a path-following task from three types of guidance. Local-adaptive haptic guidance shows the similar positive effect to haptic guidance in terms of reducing completion time. Moreover, the trainee with local-adaptive haptic guidance perform the task more smoothly than the trainee with haptic guidance. This research provides suggestions for the way to reduce the hampering effect of haptic guidance.

목차

Abstract
1. INTRODUCTION
2. METHOD
3. TRAINING RESULT
4. CONCLUSION
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