结合触觉和惯性动作捕捉增强双臂机器人的远程控制

IF 2.2 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Vicent Girbés-Juan, Vinicius Schettino, Luis Gracia, J. Ernesto Solanes, Yiannis Demiris, Josep Tornero
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引用次数: 4

摘要

在物体之间有接触的任务中,例如表面处理(擦拭,抛光,磨损,打磨等),特别是当所涉及的物体的位置未知或高度不准确时,因为它们是移动的,就像汽车工业生产线上的车身一样。这些应用需要人的适应性和机器人的精度。然而,由于安全问题,在大多数情况下共享相同的工作空间是不可能的。因此,本文介绍了一种结合触觉和惯性运动捕捉系统的多模态遥操作系统。人类操作员通过触觉反馈获得触觉,而使用动作捕捉设备可以实现更自然的动作。还引入了视觉反馈辅助来增强沉浸感。使用百特双臂机器人提供更大的灵活性和机动性,允许同时执行两项独立的操作。已经进行了几项测试来评估拟议的系统。实验结果表明,该方法缩短了任务时间,提高了整体性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combining haptics and inertial motion capture to enhance remote control of a dual-arm robot

High dexterity is required in tasks in which there is contact between objects, such as surface conditioning (wiping, polishing, scuffing, sanding, etc.), specially when the location of the objects involved is unknown or highly inaccurate because they are moving, like a car body in automotive industry lines. These applications require the human adaptability and the robot accuracy. However, sharing the same workspace is not possible in most cases due to safety issues. Hence, a multi-modal teleoperation system combining haptics and an inertial motion capture system is introduced in this work. The human operator gets the sense of touch thanks to haptic feedback, whereas using the motion capture device allows more naturalistic movements. Visual feedback assistance is also introduced to enhance immersion. A Baxter dual-arm robot is used to offer more flexibility and manoeuvrability, allowing to perform two independent operations simultaneously. Several tests have been carried out to assess the proposed system. As it is shown by the experimental results, the task duration is reduced and the overall performance improves thanks to the proposed teleoperation method.

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来源期刊
Journal on Multimodal User Interfaces
Journal on Multimodal User Interfaces COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
6.90
自引率
3.40%
发文量
12
审稿时长
>12 weeks
期刊介绍: The Journal of Multimodal User Interfaces publishes work in the design, implementation and evaluation of multimodal interfaces. Research in the domain of multimodal interaction is by its very essence a multidisciplinary area involving several fields including signal processing, human-machine interaction, computer science, cognitive science and ergonomics. This journal focuses on multimodal interfaces involving advanced modalities, several modalities and their fusion, user-centric design, usability and architectural considerations. Use cases and descriptions of specific application areas are welcome including for example e-learning, assistance, serious games, affective and social computing, interaction with avatars and robots.
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