[{"data":1,"prerenderedAt":222},["ShallowReactive",2],{"publication-2025\u002Fsurvive-against-degradations-an-insight-of-lidar-imu-slam-under-feature-degradat":3,"publication-members":55},{"_path":4,"_dir":5,"_draft":6,"_partial":6,"_locale":7,"title":8,"description":9,"_hidden":6,"authors":10,"authors_orcid":17,"year":24,"doi":25,"openalex_id":26,"venue":19,"abstract_screenshot":19,"keywords":27,"body":35,"_type":48,"_id":49,"_source":50,"_file":51,"_stem":52,"_extension":53,"locale":54},"\u002Fpublications\u002F2025\u002Fsurvive-against-degradations-an-insight-of-lidar-imu-slam-under-feature-degradat","2025",false,"","Survive Against Degradations: An Insight of LiDAR-IMU SLAM Under Feature Degradations","LiDAR-based Simultaneous Localization and Mapping (SLAM) plays a crucial role in autonomous navigation, particularly in GPS-denied environments. However, the performance of LiDAR SLAM is significantly impacted by geometric feature degradation, such as in long corridors and staircases, where insufficient structural variation leads to localization drift and mapping inconsistencies. This study evaluates the robustness and accuracy of four state-of-the-art LiDAR SLAM algorithms—Fast-LIO, Faster-LIO, Point-LIO, and PV-LIO—using a public dataset recorded in feature-degraded environments, namely GEODE. Experimental results indicate that PV-LIO outperforms the other algorithms, demonstrating superior accuracy and robustness in challenging conditions. These results offer important insights into the constraints of existing LiDAR SLAM methods and serve as a guideline for selecting algorithms in environments with low features.",[11,12,13,14,15,16],"Yang, Mengshen","Jia, Fuhua","Hou, Xing","Wang, Xiuqi","Rushworth, Adam","Sun, Xu",[18,19,20,21,22,23],"0000-0002-8355-2227",null,"0009-0002-5500-8803","0000-0003-0328-6182","0000-0003-3803-7549","0000-0002-2340-7095",2025,"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcvidl65390.2025.11085801","W4412623905",[28,29,30,31,32,33,34],"Inertial measurement unit","Lidar","Feature (linguistics)","Computer science","Artificial intelligence","Remote 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Xiao","junlin.xiao@nottingham.edu.cn","assets\u002Fjunlin-xiao.jpg","10","content:members:research-students:junlin-xiao.md",{"_path":125,"title":98,"name":126,"role":100,"email":127,"image":128,"category":104,"order":129,"_id":130},"\u002Fmembers\u002Fresearch-students\u002Fliming-li","Liming Li","Liming.Li@nottingham.edu.cn","assets\u002Fliming-li.jpg","11","content:members:research-students:liming-li.md",{"_path":132,"title":98,"name":133,"role":100,"email":134,"image":135,"category":104,"order":136,"_id":137},"\u002Fmembers\u002Fresearch-students\u002Fmengshen-yang","Mengshen Yang","Mengshen.Yang@nottingham.edu.cn","assets\u002Fyangmengshen.png","07","content:members:research-students:mengshen-yang.md",{"_path":139,"title":110,"name":140,"role":112,"email":141,"image":142,"category":104,"order":143,"_id":144},"\u002Fmembers\u002Fresearch-students\u002Fruoxu-xiao","Ruoxu Xiao","ruoxu.Xiao@nottingham.edu.cn","assets\u002Fruoxuxiao.jpg","13","content:members:research-students:ruoxu-xiao.md",{"_path":146,"title":98,"name":147,"role":100,"email":148,"image":149,"category":104,"order":150,"_id":151},"\u002Fmembers\u002Fresearch-students\u002Ftianyi-chen","Tianyi Chen","Tianyi.Chen@nottingham.edu.cn","assets\u002Fchentianyi.png","08","content:members:research-students:tianyi-chen.md",{"_path":153,"title":154,"name":155,"role":156,"email":157,"scholar":158,"image":159,"category":160,"order":161,"orcid":22,"_id":162},"\u002Fmembers\u002Fstaff\u002Fadam-rushworth","Associate Professor in Materials and Manufacturing, PGCHE","Dr Adam Rushworth","Deputy Director of Control System 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Adjei","Richard-Amankwa.Adjei@nottingham.edu.cn","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=TshunUEAAAAJ&hl=zh-CN&oi=ao","assets\u002Frichard.webp","04","content:members:staff:richard-adjei.md",{"_path":201,"title":202,"name":203,"role":204,"email":205,"scholar":206,"orcid":207,"image":208,"category":160,"interests":209,"order":220,"_id":221},"\u002Fmembers\u002Fstaff\u002Fsalman-ijaz","Assistant Professor (Lecturer) in Control of Aerospace Systems","Dr Salman Ijaz","Director of Control System Lab","salman.ijaz@nottingham.edu.cn","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=77HGe2UAAAAJ&hl","0000-0003-1483-4754","assets\u002Fsalman-ijaz.webp",[210,211,212,213,214,215,216,217,218,219],"Fault tolerant control of aircraft","Linear parameter varying control of nonlinear systems","Fractional order modeling and control of aircraft system","Control allocation Scheme","Integral sliding mode control","Robust control","Aircraft actuation system (dissimilar redundant 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