{"title":"车轮视觉:在可变形地形上使用传感透明车轮进行车轮-地形交互测量和分析","authors":"Chen Yao;Feng Xue;Zhengyin Wang;Ye Yuan;Zheng Zhu;Liang Ding;Zhenzhong Jia","doi":"10.1109/LRA.2023.3324291","DOIUrl":null,"url":null,"abstract":"The off-road locomotion of wheeled mobile robots (WMRs) over soft terrains can be quite challenging due to the complicated wheel-terrain interaction (WTI). To avoid unforeseen non-geometric hazards such as excessive sinkage or slippage, it is crucial to oversee these terrain-related uncertainties. However, determining the appropriate sensing principle for WTI and hazard prediction remains an open problem. This letter showcases an onboard sensorized transparent wheel concept (STW) aiming to explicitly characterize the WTI over deformable terrains for rovers. The STW configuration can provide directly in-wheel interaction views, thereby offering in-wheel measurement (IM) of WTI parameters and observations of soil flow simultaneously. Unlike traditional vision-based methods, this in-situ wheel vision can characterize the entire contact geometry distributions, eliminating complicated yet inaccurate model-based stochastic estimations. Consequently, it can achieve robust and real-time (30 Hz) performance even under complex motions. We conduct representative terrain experiments on a single-wheel testbed to verify the performance of our proposed STW system, and showcase its applicability as a terramechanics test tool to remodel WTI mechanics, as seen in \n<uri>https://youtu.be/aYKW1Pp4ENw</uri>\n.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"8 12","pages":"7938-7945"},"PeriodicalIF":4.6000,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Wheel Vision: Wheel-Terrain Interaction Measurement and Analysis Using a Sensorized Transparent Wheel on Deformable Terrains\",\"authors\":\"Chen Yao;Feng Xue;Zhengyin Wang;Ye Yuan;Zheng Zhu;Liang Ding;Zhenzhong Jia\",\"doi\":\"10.1109/LRA.2023.3324291\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The off-road locomotion of wheeled mobile robots (WMRs) over soft terrains can be quite challenging due to the complicated wheel-terrain interaction (WTI). To avoid unforeseen non-geometric hazards such as excessive sinkage or slippage, it is crucial to oversee these terrain-related uncertainties. However, determining the appropriate sensing principle for WTI and hazard prediction remains an open problem. This letter showcases an onboard sensorized transparent wheel concept (STW) aiming to explicitly characterize the WTI over deformable terrains for rovers. The STW configuration can provide directly in-wheel interaction views, thereby offering in-wheel measurement (IM) of WTI parameters and observations of soil flow simultaneously. Unlike traditional vision-based methods, this in-situ wheel vision can characterize the entire contact geometry distributions, eliminating complicated yet inaccurate model-based stochastic estimations. Consequently, it can achieve robust and real-time (30 Hz) performance even under complex motions. We conduct representative terrain experiments on a single-wheel testbed to verify the performance of our proposed STW system, and showcase its applicability as a terramechanics test tool to remodel WTI mechanics, as seen in \\n<uri>https://youtu.be/aYKW1Pp4ENw</uri>\\n.\",\"PeriodicalId\":13241,\"journal\":{\"name\":\"IEEE Robotics and Automation Letters\",\"volume\":\"8 12\",\"pages\":\"7938-7945\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2023-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Robotics and Automation Letters\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10283934/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ROBOTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Robotics and Automation Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10283934/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ROBOTICS","Score":null,"Total":0}
Wheel Vision: Wheel-Terrain Interaction Measurement and Analysis Using a Sensorized Transparent Wheel on Deformable Terrains
The off-road locomotion of wheeled mobile robots (WMRs) over soft terrains can be quite challenging due to the complicated wheel-terrain interaction (WTI). To avoid unforeseen non-geometric hazards such as excessive sinkage or slippage, it is crucial to oversee these terrain-related uncertainties. However, determining the appropriate sensing principle for WTI and hazard prediction remains an open problem. This letter showcases an onboard sensorized transparent wheel concept (STW) aiming to explicitly characterize the WTI over deformable terrains for rovers. The STW configuration can provide directly in-wheel interaction views, thereby offering in-wheel measurement (IM) of WTI parameters and observations of soil flow simultaneously. Unlike traditional vision-based methods, this in-situ wheel vision can characterize the entire contact geometry distributions, eliminating complicated yet inaccurate model-based stochastic estimations. Consequently, it can achieve robust and real-time (30 Hz) performance even under complex motions. We conduct representative terrain experiments on a single-wheel testbed to verify the performance of our proposed STW system, and showcase its applicability as a terramechanics test tool to remodel WTI mechanics, as seen in
https://youtu.be/aYKW1Pp4ENw
.
期刊介绍:
The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.