{"title":"A Self‐Powered Optical Fiber Tactile Sensor With Mechanoluminescent Transduction for Robotic Grasping and Hardness Detection","authors":"Yunwen Luo, Shanshan Wang, Jianqing Chang, Yufei Zhao, Zhiqiang Wei, Bo Yin, Jing Wang, Jianjun Liu, Jun‐Cheng Zhang","doi":"10.1002/lpor.202501845","DOIUrl":null,"url":null,"abstract":"Tactile sensing is crucial for machines to interact intelligently with the physical world. Integrating mechanoluminescent (ML) materials with optical fibers presents a promising avenue for developing self‐powered tactile sensors. However, existing ML‐based optical fiber sensors suffer from inefficient signal collection or require complex demodulation strategies, thereby limiting their sensitivity and hindering compact system integration. Here, a self‐powered optical fiber tactile sensor (SOFTS) based on ML composites directly coupled to the core of a standard multimode fiber is reported. This architecture enables efficient light collection, simplifies signal demodulation, and reduces system complexity and size. The resulting sensor exhibits stable and robust ML emission in response to mechanical stimulation, without the need for external excitation. Integration of SOFTS with a robotic manipulator demonstrates real‐time tactile feedback for object grasping and hardness detection, showcasing its potential for robotics and human‐machine interfaces. This work establishes a simple, scalable, and robust platform for advancing ML‐based self‐powered optical tactile sensing technologies.","PeriodicalId":204,"journal":{"name":"Laser & Photonics Reviews","volume":"92 1","pages":""},"PeriodicalIF":10.0000,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Laser & Photonics Reviews","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1002/lpor.202501845","RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPTICS","Score":null,"Total":0}
引用次数: 0
Abstract
Tactile sensing is crucial for machines to interact intelligently with the physical world. Integrating mechanoluminescent (ML) materials with optical fibers presents a promising avenue for developing self‐powered tactile sensors. However, existing ML‐based optical fiber sensors suffer from inefficient signal collection or require complex demodulation strategies, thereby limiting their sensitivity and hindering compact system integration. Here, a self‐powered optical fiber tactile sensor (SOFTS) based on ML composites directly coupled to the core of a standard multimode fiber is reported. This architecture enables efficient light collection, simplifies signal demodulation, and reduces system complexity and size. The resulting sensor exhibits stable and robust ML emission in response to mechanical stimulation, without the need for external excitation. Integration of SOFTS with a robotic manipulator demonstrates real‐time tactile feedback for object grasping and hardness detection, showcasing its potential for robotics and human‐machine interfaces. This work establishes a simple, scalable, and robust platform for advancing ML‐based self‐powered optical tactile sensing technologies.
期刊介绍:
Laser & Photonics Reviews is a reputable journal that publishes high-quality Reviews, original Research Articles, and Perspectives in the field of photonics and optics. It covers both theoretical and experimental aspects, including recent groundbreaking research, specific advancements, and innovative applications.
As evidence of its impact and recognition, Laser & Photonics Reviews boasts a remarkable 2022 Impact Factor of 11.0, according to the Journal Citation Reports from Clarivate Analytics (2023). Moreover, it holds impressive rankings in the InCites Journal Citation Reports: in 2021, it was ranked 6th out of 101 in the field of Optics, 15th out of 161 in Applied Physics, and 12th out of 69 in Condensed Matter Physics.
The journal uses the ISSN numbers 1863-8880 for print and 1863-8899 for online publications.