{"title":"iFEM2.0:基于视觉的触觉传感器的密集三维接触力场重建与评估","authors":"Can Zhao;Jin Liu;Daolin Ma","doi":"10.1109/TRO.2024.3502197","DOIUrl":null,"url":null,"abstract":"Vision-based tactile sensors offer rich tactile information through high-resolution tactile images, enabling the reconstruction of dense contact force fields on the sensor surface. However, accurately reconstructing the 3-D contact force distribution remains a challenge. In this article, we propose the multilayer inverse finite-element method (iFEM2.0) as a robust and generalized approach to reconstruct dense contact force distribution. We systematically analyze various parameters within the iFEM2.0 framework, and determine the appropriate parameter combinations through simulation and in situ mechanical calibration. Our approach incorporates multilayer mesh constraints and ridge regularization to enhance robustness. Furthermore, as no off-the-shelf measurement equipment or criterion metrics exist for 3-D contact force distribution perception, we present a benchmark covering accuracy, fidelity, and noise resistance that can serve as a cornerstone for other future force distribution reconstruction methods. The proposed iFEM2.0 demonstrates good performance in both simulation- and experiment-based evaluations. Such dense 3-D contact force information is critical for enabling dexterous robotic manipulation that handles both rigid and soft materials.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"289-305"},"PeriodicalIF":9.4000,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"iFEM2.0: Dense 3-D Contact Force Field Reconstruction and Assessment for Vision-Based Tactile Sensors\",\"authors\":\"Can Zhao;Jin Liu;Daolin Ma\",\"doi\":\"10.1109/TRO.2024.3502197\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vision-based tactile sensors offer rich tactile information through high-resolution tactile images, enabling the reconstruction of dense contact force fields on the sensor surface. However, accurately reconstructing the 3-D contact force distribution remains a challenge. In this article, we propose the multilayer inverse finite-element method (iFEM2.0) as a robust and generalized approach to reconstruct dense contact force distribution. We systematically analyze various parameters within the iFEM2.0 framework, and determine the appropriate parameter combinations through simulation and in situ mechanical calibration. Our approach incorporates multilayer mesh constraints and ridge regularization to enhance robustness. Furthermore, as no off-the-shelf measurement equipment or criterion metrics exist for 3-D contact force distribution perception, we present a benchmark covering accuracy, fidelity, and noise resistance that can serve as a cornerstone for other future force distribution reconstruction methods. The proposed iFEM2.0 demonstrates good performance in both simulation- and experiment-based evaluations. Such dense 3-D contact force information is critical for enabling dexterous robotic manipulation that handles both rigid and soft materials.\",\"PeriodicalId\":50388,\"journal\":{\"name\":\"IEEE Transactions on Robotics\",\"volume\":\"41 \",\"pages\":\"289-305\"},\"PeriodicalIF\":9.4000,\"publicationDate\":\"2024-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Robotics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10758225/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ROBOTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Robotics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10758225/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ROBOTICS","Score":null,"Total":0}
iFEM2.0: Dense 3-D Contact Force Field Reconstruction and Assessment for Vision-Based Tactile Sensors
Vision-based tactile sensors offer rich tactile information through high-resolution tactile images, enabling the reconstruction of dense contact force fields on the sensor surface. However, accurately reconstructing the 3-D contact force distribution remains a challenge. In this article, we propose the multilayer inverse finite-element method (iFEM2.0) as a robust and generalized approach to reconstruct dense contact force distribution. We systematically analyze various parameters within the iFEM2.0 framework, and determine the appropriate parameter combinations through simulation and in situ mechanical calibration. Our approach incorporates multilayer mesh constraints and ridge regularization to enhance robustness. Furthermore, as no off-the-shelf measurement equipment or criterion metrics exist for 3-D contact force distribution perception, we present a benchmark covering accuracy, fidelity, and noise resistance that can serve as a cornerstone for other future force distribution reconstruction methods. The proposed iFEM2.0 demonstrates good performance in both simulation- and experiment-based evaluations. Such dense 3-D contact force information is critical for enabling dexterous robotic manipulation that handles both rigid and soft materials.
期刊介绍:
The IEEE Transactions on Robotics (T-RO) is dedicated to publishing fundamental papers covering all facets of robotics, drawing on interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, and beyond. From industrial applications to service and personal assistants, surgical operations to space, underwater, and remote exploration, robots and intelligent machines play pivotal roles across various domains, including entertainment, safety, search and rescue, military applications, agriculture, and intelligent vehicles.
Special emphasis is placed on intelligent machines and systems designed for unstructured environments, where a significant portion of the environment remains unknown and beyond direct sensing or control.