D. C. Demirkan, Ava Segal, Abhidipta Mallik, Sebnem Duzgun, Andrew J Petruska
{"title":"Real-Time Perception Enhancement in Obscured Environments for Underground Mine Search and Rescue Teams","authors":"D. C. Demirkan, Ava Segal, Abhidipta Mallik, Sebnem Duzgun, Andrew J Petruska","doi":"10.5772/acrt.33","DOIUrl":null,"url":null,"abstract":"First responders in underground mines face a myriad of challenges when searching for personnel in a disaster scenario. Possibly, the most acute challenge is the complete lack of visibility owing to a combination of dust, smoke, and pitch-black conditions. Moreover, the complex environment compounds the difficulty of navigating and searching the area as well as identifying hazardous conditions until in close proximity. Enhanced perception and localization technologies that enable rapid and safe disaster response could mitigate the mine rescue team’s risk and reduce response times. We developed a proof of concept perception enhancement tool for mine rescue personnel in pitch-black conditions by leveraging LiDAR, thermal camera, and data fusion to reconstruct a 3D representation of the space in real-time. This enhancement is visualized on HoloLens, allowing the responders real-time situational awareness of personnel, walls, obstacles, or fires in otherwise opaque environments. The technology is a first step towards faster, safer, and more effective disaster response for mine rescue operations, including detection of unexpected hazards before they become imminent threats.","PeriodicalId":431659,"journal":{"name":"AI, Computer Science and Robotics Technology","volume":" 47","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AI, Computer Science and Robotics Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5772/acrt.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
First responders in underground mines face a myriad of challenges when searching for personnel in a disaster scenario. Possibly, the most acute challenge is the complete lack of visibility owing to a combination of dust, smoke, and pitch-black conditions. Moreover, the complex environment compounds the difficulty of navigating and searching the area as well as identifying hazardous conditions until in close proximity. Enhanced perception and localization technologies that enable rapid and safe disaster response could mitigate the mine rescue team’s risk and reduce response times. We developed a proof of concept perception enhancement tool for mine rescue personnel in pitch-black conditions by leveraging LiDAR, thermal camera, and data fusion to reconstruct a 3D representation of the space in real-time. This enhancement is visualized on HoloLens, allowing the responders real-time situational awareness of personnel, walls, obstacles, or fires in otherwise opaque environments. The technology is a first step towards faster, safer, and more effective disaster response for mine rescue operations, including detection of unexpected hazards before they become imminent threats.