{"title":"Shortwave infrared fusion for snow surface traversability mapping","authors":"Anthony T. Fragoso, Sarah M. Piedmont","doi":"10.1016/j.jterra.2024.101010","DOIUrl":null,"url":null,"abstract":"<div><p>Estimating the mechanical properties of snow from imagery is an essential part of over-snow vehicle autonomy. However, snow surfaces that differ widely in strength, traction, and motion resistance tend to appear a uniform bright white in visible or broadband infrared imagery, and it is difficult to determine where an oversnow vehicle should operate from imagery alone. In this work we determine the optimal fusion of filtered broadband shortwave infrared (SWIR) imagery to separate snow types with different mechanical properties by appearance. We demonstrate vastly increased discrimination skill in distinguishing snow types using a small number of SWIR cameras in both field and laboratory settings, and also identify sources of environmental context that can improve lookahead sensing for oversnow vehicles. Overall, we show that a small set of inexpensive SWIR filters is a powerful tool for over-snow autonomy and motion planning.</p></div>","PeriodicalId":50023,"journal":{"name":"Journal of Terramechanics","volume":"117 ","pages":"Article 101010"},"PeriodicalIF":2.4000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0022489824000521/pdfft?md5=760fc424eaf38e375dd88f03aa3c1289&pid=1-s2.0-S0022489824000521-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Terramechanics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022489824000521","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Estimating the mechanical properties of snow from imagery is an essential part of over-snow vehicle autonomy. However, snow surfaces that differ widely in strength, traction, and motion resistance tend to appear a uniform bright white in visible or broadband infrared imagery, and it is difficult to determine where an oversnow vehicle should operate from imagery alone. In this work we determine the optimal fusion of filtered broadband shortwave infrared (SWIR) imagery to separate snow types with different mechanical properties by appearance. We demonstrate vastly increased discrimination skill in distinguishing snow types using a small number of SWIR cameras in both field and laboratory settings, and also identify sources of environmental context that can improve lookahead sensing for oversnow vehicles. Overall, we show that a small set of inexpensive SWIR filters is a powerful tool for over-snow autonomy and motion planning.
期刊介绍:
The Journal of Terramechanics is primarily devoted to scientific articles concerned with research, design, and equipment utilization in the field of terramechanics.
The Journal of Terramechanics is the leading international journal serving the multidisciplinary global off-road vehicle and soil working machinery industries, and related user community, governmental agencies and universities.
The Journal of Terramechanics provides a forum for those involved in research, development, design, innovation, testing, application and utilization of off-road vehicles and soil working machinery, and their sub-systems and components. The Journal presents a cross-section of technical papers, reviews, comments and discussions, and serves as a medium for recording recent progress in the field.