Neuromuscular Interfacing for Advancing Kinesthetic and Teleoperated Programming by Demonstration of Collaborative Robots.

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

IEEE Transactions on Haptics Pub Date : 2024-10-21 DOI:10.1109/TOH.2024.3484373

Roberto Meattini, Armando Ameri, Alessandra Bernardini, Javier Gonzalez-Huarte, Aitor Ibarguren, Claudio Melchiorri, Gianluca Palli

{"title":"Neuromuscular Interfacing for Advancing Kinesthetic and Teleoperated Programming by Demonstration of Collaborative Robots.","authors":"Roberto Meattini, Armando Ameri, Alessandra Bernardini, Javier Gonzalez-Huarte, Aitor Ibarguren, Claudio Melchiorri, Gianluca Palli","doi":"10.1109/TOH.2024.3484373","DOIUrl":null,"url":null,"abstract":"<p><p>This study addresses the challenges of Programming by Demonstration (PbD) in the context of collaborative robots, focusing on the need to provide additional degrees of programming without hindering the user's ability to demonstrate trajectories. PbD enables an intuitive programming of robots through demonstrations, allowing non-expert users to teach robot skills without coding. The two main PbD modalities, observational and kinesthetic, have limitations when it comes to programming the diverse functionalities offered by modern collaborative robots. To overcome these limitations, the study proposes the use of a wearable human-robot interface based on surface Electromyography (sEMG) to measure the forearm's muscle co-contraction level, enabling additional programming inputs through hand stiffening level modulations without interfering with voluntary movements. Vibrotactile feedback enhances the operator's understanding of the additional programming inputs during PbD tasks. The proposed approach is demonstrated through experiments involving a collaborative robot performing an industrial wiring task. The results showcase the effectiveness and intuitiveness of the interface, allowing simultaneous programming of robot compliance and gripper grasping. The framework, applicable to both teleoperation and kinesthetic teaching, demonstrated effectively in an industrial wiring task with a 100% success rate over the group of subjects. Furthermore, the presence of vibortactile feedback showed an average decrease of programming errors of 33%, and statistical analyses confirmed the subjects' ability to correctly modulate co-contraction levels. This innovative framework augments programming by demonstration by integrating neuromuscular interfacing and introducing structured programming logics, providing an intuitive human-robot interaction for programming both gripper and compliance in teleoperation and kinesthetic teaching.</p>","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"PP ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Haptics","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/TOH.2024.3484373","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}

引用次数: 0

Abstract

This study addresses the challenges of Programming by Demonstration (PbD) in the context of collaborative robots, focusing on the need to provide additional degrees of programming without hindering the user's ability to demonstrate trajectories. PbD enables an intuitive programming of robots through demonstrations, allowing non-expert users to teach robot skills without coding. The two main PbD modalities, observational and kinesthetic, have limitations when it comes to programming the diverse functionalities offered by modern collaborative robots. To overcome these limitations, the study proposes the use of a wearable human-robot interface based on surface Electromyography (sEMG) to measure the forearm's muscle co-contraction level, enabling additional programming inputs through hand stiffening level modulations without interfering with voluntary movements. Vibrotactile feedback enhances the operator's understanding of the additional programming inputs during PbD tasks. The proposed approach is demonstrated through experiments involving a collaborative robot performing an industrial wiring task. The results showcase the effectiveness and intuitiveness of the interface, allowing simultaneous programming of robot compliance and gripper grasping. The framework, applicable to both teleoperation and kinesthetic teaching, demonstrated effectively in an industrial wiring task with a 100% success rate over the group of subjects. Furthermore, the presence of vibortactile feedback showed an average decrease of programming errors of 33%, and statistical analyses confirmed the subjects' ability to correctly modulate co-contraction levels. This innovative framework augments programming by demonstration by integrating neuromuscular interfacing and introducing structured programming logics, providing an intuitive human-robot interaction for programming both gripper and compliance in teleoperation and kinesthetic teaching.

查看原文本刊更多论文

通过演示协作机器人，建立神经肌肉接口，促进运动学和远程操作编程。

本研究探讨了协作机器人中演示编程（PbD）所面临的挑战，重点是在不妨碍用户演示轨迹的情况下提供额外编程度的必要性。PbD 可通过演示对机器人进行直观编程，让非专业用户无需编码即可教授机器人技能。在对现代协作机器人提供的各种功能进行编程时，两种主要的 PbD 模式（观察式和运动式）存在局限性。为了克服这些局限性，该研究建议使用基于表面肌电图（sEMG）的可穿戴式人机界面来测量前臂肌肉的协同收缩水平，从而在不干扰自主运动的情况下，通过调节手部僵硬程度来实现额外的编程输入。振动反馈增强了操作员对 PbD 任务中额外编程输入的理解。我们通过实验演示了所提出的方法，实验涉及执行工业布线任务的协作机器人。实验结果展示了界面的有效性和直观性，允许同时进行机器人顺应性和抓手抓取编程。该框架既适用于远程操作，也适用于运动学教学，在工业布线任务中发挥了有效作用，受试者的成功率达到 100%。此外，振动触觉反馈的存在使编程错误平均减少了 33%，统计分析证实了受试者正确调节协同收缩水平的能力。这一创新框架通过整合神经肌肉接口和引入结构化编程逻辑来增强示范编程，为远程操作和运动学教学中的抓手和顺应性编程提供了直观的人机交互方式。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

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.