[{"data":1,"prerenderedAt":408},["ShallowReactive",2],{"method-hinduja2019degeneracy":3},{"method":4,"reference":50,"equipment":70,"figures":93,"results":94},{"id":5,"label":6,"shortName":7,"title":8,"year":9,"era":10,"cluster":11,"scope":12,"keyIdeaZh":13,"keyIdeaEn":14,"fulltextStatus":15,"publicationStatus":16,"recommendation":17,"constructionRelevance":18,"validationEnvironment":19,"strengths":22,"limitations":26,"sensors":31,"platform":36,"estimator":38,"association":39,"timeModel":40,"deskew":41,"loopClosure":42,"globalOptimization":43,"mapRepresentation":44,"prior":45,"outputGeometry":46,"compute":41,"codeUrl":47,"codeLicense":48,"relatedVersions":49},"hinduja2019degeneracy","Hinduja et al., 2019","Degeneracy-aware factors","Degeneracy-Aware Factors with Applications to Underwater SLAM",2019,"recent","C13","registration_component","本文把退化感知延伸到位姿圖：點對面 ICP 每次迭代以最大與最小特徵值的比值（條件數）作為動態門檻，只沿受約束方向更新（沿用 Zhang 等人的解重映射）；再把結果以部分迴圈閉合因子加入位姿圖，只約束 X、Y 與偏航，深度、俯仰與滾轉則交由深度計與航姿參考系統的先驗處理。作者以 DIDSON 聲納子地圖的水下建圖在模擬與實際資料驗證，顯示可抵抗導航漂移並拒絕退化環境中的不良迴圈閉合（Sec. III, IV）。","Degeneracy-aware ICP plus partially constrained loop-closure factors that only constrain well-conditioned directions in pose-graph SLAM.","full_text_reviewed","peer_reviewed_published","background","原文為水下聲納；在 X-ICP 的工地比較中作為基線（見 tuna2024xicp）。",[20,21],"simulation","infrastructure",[23,24,25],"Lower RMSE than point-to-plane ICP with odometry prior and full loop-closure factors (PTP-OP) on both simulated datasets: pilings 0.173 vs 0.618, propeller 0.168 vs 0.429; odometry alone gave 0.183 and 0.346 (Table I)","Rejects poorly constrained loop closures: 9 accepted versus 34 for PTP-OP on pilings and 17 versus 45 on the propeller, with identical parameters (Sec. IV-C)","On real SS Curtis running gear and pier pilings data with added noise, maps were visually closer to the noise-free odometry reference than Teixeira et al.'s submap SLAM (Sec. IV-D, Figs. 7 and 9)",[27,28,29,30],"X-ICP reports that this method relies more on the odometry prior and showed blurred structures at the Rümlang construction site due to prior drift (Tuna et al. 2024, Sec. VII-E)","Different environments benefit from different threshold values; automatic threshold selection from sensor data is left to future work (Sec. V)","Real-world evaluation is qualitative and uses the noise-free odometry-only solution as reference, not independent ground truth (Sec. IV-D)","The partial loop-closure factor covers at most 3 DoF (X, Y, yaw) because depth, pitch and roll come from the vehicle's drift-free sensors (Sec. IV-B2)",[32,33,34,35],"multibeam imaging sonar (DIDSON, 96 beams, profiling mode with a concentrator lens giving 1 degree vertical FOV)","DVL (Teledyne\u002FRDI Workhorse Navigator, 1.2 MHz)","AHRS with Honeywell HG1700 IMU","depth sensor (Paroscientific Digiquartz)",[37,20],"underwater vehicle (Bluefin HAUV)","pose-graph optimization with partially constrained loop-closure factors","degeneracy-aware point-to-plane ICP (PCL-based) with solution remapping between sonar submaps","discrete poses","not_reported","ICP loop closures inserted as partial factors constraining only well-constrained directions","pose graph optimization with the iSAM library (Euler-angle poses, 3-DoF XYH odometry factors, unary ZPR factors, partial loop-closure factors)","volumetric sonar submaps in a submap-based pose graph","vehicle odometry from DVL and AHRS dead reckoning (X, Y, yaw drift); drift-free depth, pitch and roll from the depth sensor and AHRS appended as whitened prior rows to the ICP linear system and as unary ZPR factors in the pose graph","submap-based 3D reconstruction (point clouds) and poses",null,"not_verified",[],{"id":5,"kind":51,"shortName":7,"title":8,"authors":52,"year":9,"venue":56,"venueType":57,"publisher":58,"volumeIssuePages":59,"doi":60,"arxivId":47,"url":61,"firstPublicDate":62,"publicationStatus":16,"metadataStatus":63,"fulltextStatus":15,"era":10,"classicReason":64,"codeUrl":47,"cluster":11,"topics":65,"mdpi":66,"verification":67,"label":6,"fulltextRoute":68,"versionRead":69,"addedByCensus":66},"component",[53,54,55],"Akshay Hinduja","Bing-Jui Ho","Michael Kaess","2019 IEEE\u002FRSJ International Conference on Intelligent Robots and Systems (IROS)","conference","IEEE","pp. 1293-1299","10.1109\u002Firos40897.2019.8968577","https:\u002F\u002Fdoi.org\u002F10.1109\u002FIROS40897.2019.8968577","2019-11","metadata_verified","not_applicable",[11],false,"corrected","author copy","author copy Hinduja19iros.pdf from the Kaess lab publication page (7 pages, IROS 2019 conference layout); not compared page by page with the IEEE VoR",[71,77,82,86,90],{"category":72,"model":73,"canonical":73,"role":74,"dataset":47,"specs":75,"locator":76},"platform","Bluefin Hovering Autonomous Underwater Vehicle (HAUV)","method input","five thrusters controlling all DoF except roll and pitch; onboard odometry from fused navigation sensors","Sec. IV-A, Fig. 3",{"category":78,"model":79,"canonical":79,"role":74,"dataset":47,"specs":80,"locator":81},"other","DIDSON (dual-frequency identification sonar)","96 beams, 2D transducer array; concentrator lens reduces vertical FOV to 1 degree (profiling mode); fixed number of profile scans per submap","Sec. IV-A",{"category":78,"model":83,"canonical":84,"role":74,"dataset":47,"specs":85,"locator":81},"Teledyne\u002FRDI Workhorse Navigator Doppler velocity log","Livox Tele","1.2 MHz",{"category":87,"model":88,"canonical":88,"role":74,"dataset":47,"specs":89,"locator":81},"imu","Honeywell HG1700 (in the AHRS)","AHRS gives drift-free pitch and roll",{"category":78,"model":91,"canonical":91,"role":74,"dataset":47,"specs":92,"locator":81},"Paroscientific Digiquartz depth sensor","drift-free depth measurement",[],{"totalRows":95,"groupCount":96,"groups":97,"others":386},31,8,[98,212,283,340],{"slug":99,"group":100,"sourceId":101,"sourceLabel":102,"table":103,"selfRows":104,"metrics":105,"seqs":123,"entrants":132,"cells":141,"outcomes":205,"locators":206,"hardware":207,"wordings":208,"notes":209},"tuna2024xicp-table-i","tuna2024xicp:Table I","tuna2024xicp","Tuna et al., 2024","Table I",9,[106,110,112,115,116,118,119,120,121],{"label":107,"unit":108,"statistic":109,"alignment":41},"APE Translation mu(sigma) [m]","m","mean",{"label":107,"unit":108,"statistic":111,"alignment":41},"std",{"label":113,"unit":114,"statistic":109,"alignment":41},"APE Rotation mu(sigma) [deg]","deg",{"label":113,"unit":114,"statistic":111,"alignment":41},{"label":107,"unit":108,"statistic":109,"alignment":117},"first-pose",{"label":107,"unit":108,"statistic":111,"alignment":117},{"label":113,"unit":114,"statistic":109,"alignment":117},{"label":113,"unit":114,"statistic":111,"alignment":117},{"label":122,"unit":108,"statistic":41,"alignment":41},"Last Position Error [m]",[124,128,130],{"dataset":125,"sequence":126,"environment":127},"Seemuhle underground mine (authors' data)","VLP-16 run; first 15 m alignment","underground mine tunnel",{"dataset":125,"sequence":129,"environment":127},"VLP-16 run; origin alignment",{"dataset":125,"sequence":131,"environment":127},"VLP-16 run; full 521.8 m traverse",[133,136,139],{"name":134,"methodId":101,"linkable":135,"proposed":135,"self":66},"X-ICP (Proposed)",true,{"name":137,"methodId":138,"linkable":135,"proposed":66,"self":66},"Zhang et al. [12]","zhang2016degeneracy",{"name":140,"methodId":5,"linkable":135,"proposed":66,"self":135},"Hinduja et al. [17]",[142,146,149,152,155,158,161,164,167,169,171,173,175,177,179,181,183,185,187,189,191,193,195,197,199,201,203],[143,143,143,144,145,143,145,145,143],0,2.05,-1,[143,147,143,148,145,143,145,145,147],1,1.23,[143,150,143,151,145,143,145,145,147],2,2.55,[143,153,143,154,145,143,145,145,147],3,0.76,[143,156,147,157,145,143,145,145,147],4,2.45,[143,159,147,160,145,143,145,145,147],5,1.35,[143,162,147,163,145,143,145,145,147],6,2.5,[143,165,147,166,145,143,145,145,147],7,1.03,[143,96,150,168,145,143,145,145,147],0.27,[147,143,143,170,145,143,145,145,147],3.36,[147,147,143,172,145,143,145,145,147],1.74,[147,150,143,174,145,143,145,145,147],4.06,[147,153,143,176,145,143,145,145,147],1.37,[147,156,147,178,145,143,145,145,147],3.73,[147,159,147,180,145,143,145,145,147],1.8,[147,162,147,182,145,143,145,145,147],4.11,[147,165,147,184,145,143,145,145,147],1.52,[147,96,150,186,145,143,145,145,147],6.37,[150,143,143,188,145,143,145,145,147],5.79,[150,147,143,190,145,143,145,145,147],5.26,[150,150,143,192,145,143,145,145,147],7.67,[150,153,143,194,145,143,145,145,147],4.72,[150,156,147,196,145,143,145,145,147],8.16,[150,159,147,198,145,143,145,145,147],4.83,[150,162,147,200,145,143,145,145,147],8.03,[150,165,147,202,145,143,145,145,147],4.73,[150,96,150,204,145,143,145,145,147],24.17,[],[103],[],[],[210,211],"Seemuhle underground mine, ANYmal with VLP-16, 521.8 m; APE via EVO against Leica RTC 360 ground truth, mu (sigma); 'first 15 m' = trajectory aligned on the first 15 m (about 200 poses), 'origin' = aligned at the first pose; plus last-position error","Same setting as other Table I rows",{"slug":213,"group":214,"sourceId":215,"sourceLabel":216,"table":217,"selfRows":96,"metrics":218,"seqs":233,"entrants":241,"cells":250,"outcomes":277,"locators":278,"hardware":279,"wordings":280,"notes":281},"hatleskog2024probdegen-table-ii","hatleskog2024probdegen:Table II","hatleskog2024probdegen","Hatleskog & Alexis, 2024","Table II",[219,221,223,225,227,229,231],{"label":220,"unit":108,"statistic":109,"alignment":41},"APE [m], mean (SD 0.13)",{"label":222,"unit":114,"statistic":109,"alignment":41},"APE [deg], mean (SD 0.63)",{"label":224,"unit":108,"statistic":109,"alignment":41},"RPE [m], mean (SD 0.01)",{"label":226,"unit":114,"statistic":109,"alignment":41},"RPE [deg], mean (SD 0.31)",{"label":228,"unit":108,"statistic":109,"alignment":41},"APE [m], mean (SD 0.01)",{"label":230,"unit":114,"statistic":109,"alignment":41},"APE [deg], mean (SD 0.18)",{"label":232,"unit":114,"statistic":109,"alignment":41},"RPE [deg], mean (SD 0.19)",[234,238],{"dataset":235,"sequence":236,"environment":237},"Seemühle Mine","full trajectory","abandoned underground mine, self-similar tunnel",{"dataset":235,"sequence":239,"environment":240},"non-tunnel segments","underground mine, segments before and after the tunnel",[242,244,246,248],{"name":243,"methodId":138,"linkable":135,"proposed":66,"self":66},"Zhang [14]",{"name":245,"methodId":5,"linkable":135,"proposed":66,"self":135},"Hinduja [15]",{"name":247,"methodId":215,"linkable":135,"proposed":135,"self":66},"Ours",{"name":249,"methodId":47,"linkable":66,"proposed":66,"self":66},"Lee [19] (Switch-SLAM)",[251,253,255,257,259,260,261,262,264,266,267,269,270,271,272,274,275,276],[143,143,143,252,145,143,145,145,143],0.57,[147,143,143,254,145,143,145,145,143],0.18,[147,147,143,256,145,143,145,145,143],1.28,[150,150,143,258,145,143,145,145,143],0.01,[143,150,143,258,145,143,145,145,143],[147,150,143,258,145,143,145,145,143],[153,150,143,258,145,143,145,145,143],[147,153,143,263,145,143,145,145,143],0.23,[150,156,147,265,145,143,145,145,143],0.02,[147,156,147,265,145,143,145,145,143],[150,159,147,268,145,143,145,145,143],0.38,[147,159,147,268,145,143,145,145,143],[150,150,147,258,145,143,145,145,143],[147,150,147,258,145,143,145,145,143],[150,162,147,273,145,143,145,145,143],0.12,[143,162,147,273,145,143,145,145,143],[147,162,147,273,145,143,145,145,143],[153,162,147,273,145,143,145,145,143],[],[217],[],[],[282],"Seemühle mine, mean (SD) APE and RPE",{"slug":284,"group":285,"sourceId":215,"sourceLabel":216,"table":103,"selfRows":156,"metrics":286,"seqs":290,"entrants":305,"cells":310,"outcomes":327,"locators":330,"hardware":335,"wordings":336,"notes":337},"hatleskog2024probdegen-table-i","hatleskog2024probdegen:Table I",[287],{"label":288,"unit":289,"statistic":41,"alignment":289},"degeneracy-induced drift (qualitative)","none",[291,295,297,301],{"dataset":292,"sequence":293,"environment":294},"Rümlang Construction Site","exp. 1 (VLP-16, FOV cut to 180 deg)","large open area of a construction site",{"dataset":235,"sequence":296,"environment":127},"exp. 2 (VLP-16, full FOV)",{"dataset":298,"sequence":299,"environment":300},"RelyOn Nutec","exp. 3 (OS0-64, FOV cut to 180 deg)","cylindrical tank, radius 8 m, height 16 m",{"dataset":302,"sequence":303,"environment":304},"Fyllingsdalen Bicycle Tunnel","exp. 4 (OS0-128, full FOV)","500 m straight bicycle tunnel section",[306,307,308,309],{"name":247,"methodId":215,"linkable":135,"proposed":135,"self":66},{"name":243,"methodId":138,"linkable":135,"proposed":66,"self":66},{"name":245,"methodId":5,"linkable":135,"proposed":66,"self":135},{"name":249,"methodId":47,"linkable":66,"proposed":66,"self":66},[311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326],[143,143,143,47,143,143,145,145,143],[147,143,143,47,147,143,145,145,147],[150,143,143,47,147,143,145,145,147],[153,143,143,47,147,143,145,145,147],[143,143,147,47,143,147,145,145,147],[147,143,147,47,147,147,145,145,147],[150,143,147,47,143,147,145,145,147],[153,143,147,47,147,147,145,145,147],[143,143,150,47,143,150,145,145,147],[147,143,150,47,147,150,145,145,147],[150,143,150,47,147,150,145,145,147],[153,143,150,47,147,150,145,145,147],[143,143,153,47,143,153,145,145,147],[147,143,153,47,147,153,145,145,147],[150,143,153,47,143,153,145,145,147],[153,143,153,47,147,153,145,145,147],[328,329],"no degeneracy-induced drift","degeneracy-induced drift",[331,332,333,334],"Table I, Fig. 2","Table I, Fig. 3","Table I, Fig. 4","Table I, Fig. 5",[],[],[338,339],"Qualitative presence or absence of degeneracy-induced drift in partial maps; no numeric values","Qualitative drift check",{"slug":341,"group":342,"sourceId":101,"sourceLabel":102,"table":217,"selfRows":156,"metrics":343,"seqs":350,"entrants":353,"cells":357,"outcomes":379,"locators":380,"hardware":381,"wordings":382,"notes":383},"tuna2024xicp-table-ii","tuna2024xicp:Table II",[344,346,347,349],{"label":345,"unit":108,"statistic":109,"alignment":289},"RPE Translation mu(sigma) [m] per 10 m",{"label":345,"unit":108,"statistic":111,"alignment":289},{"label":348,"unit":114,"statistic":109,"alignment":289},"RPE Rotation mu(sigma) [deg] per 10 m",{"label":348,"unit":114,"statistic":111,"alignment":289},[351],{"dataset":125,"sequence":352,"environment":127},"VLP-16 run",[354,355,356],{"name":134,"methodId":101,"linkable":135,"proposed":135,"self":66},{"name":137,"methodId":138,"linkable":135,"proposed":66,"self":66},{"name":140,"methodId":5,"linkable":135,"proposed":66,"self":135},[358,360,361,363,365,367,369,371,373,375,376,377],[143,143,143,359,145,143,145,145,143],0.17,[143,147,143,273,145,143,145,145,147],[143,150,143,362,145,143,145,145,147],0.86,[143,153,143,364,145,143,145,145,147],0.42,[147,143,143,366,145,143,145,145,147],0.2,[147,147,143,368,145,143,145,145,147],0.14,[147,150,143,370,145,143,145,145,147],0.93,[147,153,143,372,145,143,145,145,147],0.51,[150,143,143,374,145,143,145,145,147],0.26,[150,147,143,368,145,143,145,145,147],[150,150,143,256,145,143,145,145,147],[150,153,143,378,145,143,145,145,147],0.74,[],[217],[],[],[384,385],"RPE per 10 m traversed distance, Seemuhle mine with VLP-16, mu (sigma)","Same setting as other Table II rows",[387,393,398,403],{"group":388,"slug":389,"sourceLabel":6,"table":103,"selfRows":150,"datasets":390},"hinduja2019degeneracy:Table I","hinduja2019degeneracy-table-i",[391,392],"simulated pilings","simulated propeller",{"group":394,"slug":395,"sourceLabel":6,"table":396,"selfRows":150,"datasets":397},"hinduja2019degeneracy:Text Sec. IV-C","hinduja2019degeneracy-text-sec-iv-c","Text Sec. IV-C",[391,392],{"group":399,"slug":400,"sourceLabel":216,"table":401,"selfRows":147,"datasets":402},"hatleskog2024probdegen:Text Sec. IV-D","hatleskog2024probdegen-text-sec-iv-d","Text Sec. IV-D",[298],{"group":404,"slug":405,"sourceLabel":216,"table":406,"selfRows":147,"datasets":407},"hatleskog2024probdegen:Text Sec. IV-E","hatleskog2024probdegen-text-sec-iv-e","Text Sec. IV-E",[302],1790510663885]