Enhance Kinesthetic Experience in Perceptual Learning for Welding Motor Skill Acquisition With Virtual Reality and Robot-Based Haptic Guidance

IF 2.4 3区 计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS
Yang Ye;Pengxiang Xia;Fang Xu;Jing Du
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引用次数: 0

Abstract

Welding is an important operation in many industries, including construction and manufacturing, which requires extensive training and practices. Although welding simulators have been used to accommodate welding training, it is still challenging to enable novice trainees to effectively understand the kinesthetic experience of the expert in an egocentric manner, such as the proper way of force exertion in complex welding operations. This study implements a robot-assisted perceptual learning system to transfer the expert welders’ experience to trainees, including both the positional and force control actions. A human-subject experiment (N = 30) was performed to understand the motor skill acquisition process. Three conditions (control, robotic positional guidance with force visualization, and force perceptual learning with position visualization) were tested to evaluate the role of robotic guidance in welding motion control and force exertion. The results indicated various benefits related to task completion time and force control accuracy under the robotic guidance. The findings can inspire the design of future welding training systems enabled by external robotic systems.
利用虚拟现实和基于机器人的触觉引导,在焊接运动技能学习的感知学习中增强运动体验。
焊接是许多行业(包括建筑业和制造业)的一项重要操作,需要大量的培训和实践。虽然焊接模拟器已被用于适应焊接培训,但要让新手学员以自我为中心的方式有效理解专家的动觉体验,例如在复杂的焊接操作中正确的用力方式,仍然具有挑战性。本研究采用机器人辅助感知学习系统,将焊接专家的经验传授给学员,包括位置和力度控制动作。为了解运动技能的习得过程,我们进行了一项人类-受试者实验(N = 30)。实验测试了三种情况(对照组、带有力可视化功能的机器人位置引导组和带有位置可视化功能的力感知学习组),以评估机器人引导在焊接动作控制和用力方面的作用。结果表明,在机器人引导下,任务完成时间和力控制精度都有不同程度的提高。这些发现可为未来设计由外部机器人系统支持的焊接培训系统提供启发。
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来源期刊
IEEE Transactions on Haptics
IEEE Transactions on Haptics COMPUTER SCIENCE, CYBERNETICS-
CiteScore
5.90
自引率
13.80%
发文量
109
审稿时长
>12 weeks
期刊介绍: IEEE Transactions on Haptics (ToH) is a scholarly archival journal that addresses the science, technology, and applications associated with information acquisition and object manipulation through touch. Haptic interactions relevant to this journal include all aspects of manual exploration and manipulation of objects by humans, machines and interactions between the two, performed in real, virtual, teleoperated or networked environments. Research areas of relevance to this publication include, but are not limited to, the following topics: Human haptic and multi-sensory perception and action, Aspects of motor control that explicitly pertain to human haptics, Haptic interactions via passive or active tools and machines, Devices that sense, enable, or create haptic interactions locally or at a distance, Haptic rendering and its association with graphic and auditory rendering in virtual reality, Algorithms, controls, and dynamics of haptic devices, users, and interactions between the two, Human-machine performance and safety with haptic feedback, Haptics in the context of human-computer interactions, Systems and networks using haptic devices and interactions, including multi-modal feedback, Application of the above, for example in areas such as education, rehabilitation, medicine, computer-aided design, skills training, computer games, driver controls, simulation, and visualization.
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