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Effect of local-adaptive haptic guidance on a path-following task

Hee-Seung Moon, Jiwon Seo

发表年份
2017
引用次数
3

摘要

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 local-adaptive 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.

关键词

Haptic technologyTask (project management)Guidance systemComputer scienceStereotaxyRobotPath (computing)SimulationArtificial intelligenceHuman–computer interaction

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