ViTac: Visual-Tactile Synergy for Handling Flexible Materials

ViTac：处理柔性材料的视觉-触觉协同

• 批准号: EP/T033517/1
• 负责人: Shan Luo
• 金额: $ 51.29万
• 依托单位: University of Liverpool
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FT033517%2F1
• 关键词: ViTac; Visual; Tactile; Synergy; Handling

Handling flexible materials is common in industrial, domestic and retail applications, e.g., evaluating new fabric products in the fashion industry, sorting clothes at home and replenishing shelves in a clothing store. Such tasks have been highly dependent on human labour and are still challenging for autonomous systems due to the complex dynamics of flexible materials. This proposal aims to develop a new visuo-tactile integration mechanism for estimating the dynamic states and properties of flexible materials while they are being manipulated by robot hands. This technique offers the potential to revolutionise the autonomous systems for handling flexible materials, allowing inclusion of their automated handling in larger automated production processes and process management systems. While the initial system to be developed in this work is for handling the textiles, the same technology would have the potential to be applied in handling other flexible materials including fragile products in the food industry, flexible objects in manufacturing and hazardous materials in healthcare.

处理柔性材料在工业、家庭和零售应用中是常见的，例如，评估时装业的新面料产品，在家里整理衣服，在服装店补充货架。这些任务高度依赖于人力，由于柔性材料的复杂动力学，对于自主系统来说仍然具有挑战性。该建议旨在开发一种新的视觉-触觉集成机制，用于估计柔性材料的动态状态和特性，同时它们被机器人手操纵。这种技术有可能彻底改变处理柔性材料的自动化系统，使其能够在更大的自动化生产过程和过程管理系统中自动处理。虽然这项工作中开发的初始系统是用于处理纺织品，但同样的技术也有可能应用于处理其他柔性材料，包括食品工业中的易碎产品，制造业中的柔性物体和医疗保健中的危险材料。

项目成果

Facial Expressions-Controlled Flight Game With Haptic Feedback for Stroke Rehabilitation: A Proof-of-Concept Study

• DOI: 10.1109/lra.2022.3170214
• 发表时间: 2022-07
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: Min Li;Zonglin Wu;Chen-Guang Zhao;Hua Yuan;Tianci Wang;Jun Xie;Guanghua Xu;Shan Luo

Generation of GelSight Tactile Images for Sim2Real Learning

• DOI: 10.1109/lra.2021.3063925
• 发表时间: 2021-04-01
• 期刊: IEEE ROBOTICS AND AUTOMATION LETTERS
• 影响因子: 5.2
• 作者: Gomes, Daniel Fernandes;Paoletti, Paolo;Luo, Shan
• 通讯作者: Luo, Shan

Where Shall I Touch? Vision-Guided Tactile Poking for Transparent Object Grasping

• DOI: 10.1109/tmech.2022.3201057
• 发表时间: 2022-08
• 期刊: IEEE/ASME Transactions on Mechatronics
• 作者: Jiaqi Jiang;G. Cao;Aaron Butterworth;Thanh-Toan Do;Shan Luo

A CNN-LSTM model for six human ankle movements classification on different loads.

• DOI: 10.3389/fnhum.2023.1101938
• 发表时间: 2023
• 期刊: Frontiers in human neuroscience
• 影响因子: 2.9

Reducing Tactile Sim2Real Domain Gaps via Deep Texture Generation Networks

通过深度纹理生成网络减少触觉 Sim2Real 域间隙

• DOI: 10.1109/icra46639.2022.9811801
• 发表时间: 2022
• 作者: Jianu T