可重构触觉反馈:综合设计与控制框架

IF 6.1 Q1 AUTOMATION & CONTROL SYSTEMS
Serhat Demirtas, Anke van Oosterhout, Rohit Kadungamparambil John, Jamie Paik
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引用次数: 0

摘要

触觉界面通过模拟真实世界的触摸交互和提供触觉反馈来增强虚拟现实体验,同时还通过加速恢复的交互式系统支持康复。然而,目前的触觉技术通常是为特定用途而构建的,这突出了对允许可重构设计和控制的通用方法的需求。本文介绍了模块化软机器人装置设计与控制的一个综合框架。这些模块可以组合成各种配置,以开发各种触觉设备,能够动态修改其刚度和形状,以适应不同的应用,包括在虚拟环境中提供触觉反馈,并帮助个人手部康复需求。报告了这些模块的设计方法,并提出了两个潜在的用例。此外,还展示了如何直观地控制模块化软机器人设备,监控其状态,并使用机器学习模型的有限传感能力来解释与用户和周围环境的交互。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Reconfigurable Haptic Feedback: Comprehensive Design and Control Framework

Reconfigurable Haptic Feedback: Comprehensive Design and Control Framework

Reconfigurable Haptic Feedback: Comprehensive Design and Control Framework

Reconfigurable Haptic Feedback: Comprehensive Design and Control Framework

Reconfigurable Haptic Feedback: Comprehensive Design and Control Framework

Haptic interfaces enhance the virtual reality experience by emulating real-world touch-based interactions and delivering tactile feedback, while also supporting rehabilitation through interactive systems that speed up recovery. However, current haptic technologies are often built for specific uses, highlighting the need for generalized methods that allow for reconfigurable design and control. In this article, a comprehensive framework is introduced for the design and control of modular soft robotic devices. These modules can be combined in various configurations to develop a wide range of haptic devices capable of dynamically modifying their stiffness and shape to accommodate different applications, including providing haptic feedback in virtual environments and assisting individuals with hand rehabilitation needs. The design methodology of these modules is reported and two potential use cases are presented. Furthermore, it is demonstrated that how it is possible to intuitively control the modular soft robotic devices, monitor their state, and use limited sensing capability with machine learning models to enable interpretations of interactions with users and the surrounding environment.

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来源期刊
CiteScore
1.30
自引率
0.00%
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