[{"data":1,"prerenderedAt":1272},["ShallowReactive",2],{"method-okvis2015":3},{"method":4,"reference":57,"equipment":81,"figures":122,"results":123},{"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":25,"sensors":30,"platform":34,"estimator":37,"association":38,"timeModel":39,"deskew":40,"loopClosure":41,"globalOptimization":42,"mapRepresentation":43,"prior":44,"outputGeometry":45,"compute":46,"codeUrl":47,"codeLicense":48,"relatedVersions":49},"okvis2015","Leutenegger et al., 2015","OKVIS","Keyframe-based visual-inertial odometry using nonlinear optimization",2015,"classic","C08","odometry_with_local_mapping","OKVIS 以非線性最佳化緊耦合（tightly-coupled）融合相機重投影誤差與 IMU 慣性誤差，並只保留有限數量的關鍵影格，透過邊際化維持即時運算。關鍵影格可相隔任意時間，仍以線性化慣性項連結。作者以自製、硬體同步的雙目慣性裝置收集資料，並與 MSCKF 濾波器比較，也示範線上外參校正。","OKVIS fuses reprojection and inertial errors in a keyframe-based sliding-window nonlinear optimisation with marginalisation, evaluated on custom hardware-synchronised stereo-inertial data against an MSCKF filter.","full_text_reviewed","peer_reviewed_published","background","論文未報告營建工地測試。量化評估資料為 Vicon 室內手持繞圈（Vicon 6D 真值）、頭盔架設的自行車軌跡（7.9 km，DGPS 真值），以及繞行 ETH 主建築外部的手持戶外迴圈（620 m，DGPS 真值）；ETH 主建築室內 470 m 跨樓層行走只以圖 1 定性展示，未量化誤差。作者指出雙目版本的外參輕微誤差會表現為尺度誤差，這與工程點雲的尺度可信度相關（推論延伸）。",[20,21],"controlled_experiment","independent_reference",[23,24],"Consistently outperforms the MSCKF reference filter on the same inputs (conclusion)","Online extrinsics calibration shown; slight miscalibration manifests as scale error in stereo (conclusion)",[26,27,28,29],"Computationally more demanding than the filter baseline (conclusion)","Odometry without loop closure; drift is not globally corrected (inference from system scope)","Yaw drift is clearly present on Vicon Loops, though smaller than for the MSCKF (Sec. VII-B1)","The stereo version was slightly worse than the monocular one on the ETH Main Building loop, attributed to a slight stereo calibration mismatch; online extrinsics calibration removed the scale mismatch (Sec. VII-B3, VII-C1)",[31,32,33],"stereo","monocular camera","IMU",[35,36],"handheld (Vicon Loops; outdoor loop around ETH Main Building; indoor multi-floor ETH main building demonstration)","helmet-mounted (Bicycle Trajectory)","Nonlinear least squares (Google Ceres) over reprojection errors (keypoint std 0.8 px) and IMU error terms in a window of M keyframes plus the S most recent frames (M = 7, S = 3 in all experiments); frames leaving the window are marginalised by Schur complement with first-estimate Jacobians, dropping non-keyframe landmark observations and marginalising landmarks seen only in the oldest keyframes so that sparsity is kept; optional online camera-IMU extrinsics estimation","Customised multi-scale SSE-optimised Harris corners with BRISK descriptors oriented along the projected gravity direction; brute-force 3D-2D matching against landmarks predicted visible, outliers removed by a Mahalanobis test on the IMU-propagated pose and an OpenGV absolute-pose RANSAC; then brute-force 2D-2D matching with stereo and temporal triangulation (only points with low depth uncertainty initialised) and a relative RANSAC against the newest keyframe. In the comparison all algorithms were fed the same correspondences produced by the stereo pipeline","Discrete states at image times (position, orientation quaternion, velocity, gyro and accelerometer biases); each IMU error term integrates all IMU readings between successive camera frames with the classical Runge-Kutta method, gyro bias modelled as random walk and accelerometer bias as bounded random walk; kept keyframes may be arbitrarily far apart in time","not_applicable","none (odometry)","none","sparse landmarks in a bounded keyframe window","No prior map. Intrinsics and camera-IMU extrinsics pre-calibrated with the method of Furgale et al. (2013); IMU noise from the ADIS16448 datasheet made slightly more conservative; weak zero-mean priors on speed (3 m\u002Fs) and biases (0.1 rad\u002Fs gyro, 0.2 m\u002Fs^2 accelerometer) for robust initialisation; the online-extrinsics option uses weak priors (10 mm, 0.6 degrees)","time series of poses, velocities and IMU biases plus a sparse landmark map (conclusion)","Real time with bounded complexity (the dense part grows with O(M^3) in the number of keyframes); computationally more demanding than the MSCKF baseline; no host CPU or timing figures are reported; the sensor's FPGA can perform keypoint detection to save CPU","https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Fokvis","BSD-style 3-clause (LICENSE header)",[50,53],{"relation":51,"title":52,"doi_or_url":47},"code_release","okvis",{"relation":54,"title":55,"doi_or_url":56},"conference_version","Keyframe-Based Visual-Inertial SLAM using Nonlinear Optimization (RSS IX, 2013; authors Leutenegger, Furgale, Rabaud, Chli, Konolige, Siegwart)","10.15607\u002FRSS.2013.IX.037",{"id":5,"kind":58,"shortName":7,"title":59,"authors":60,"year":9,"venue":66,"venueType":67,"publisher":68,"volumeIssuePages":69,"doi":70,"arxivId":71,"url":72,"firstPublicDate":73,"publicationStatus":16,"metadataStatus":74,"fulltextStatus":15,"era":10,"classicReason":75,"codeUrl":47,"cluster":11,"topics":76,"mdpi":77,"verification":78,"label":6,"fulltextRoute":79,"versionRead":80,"addedByCensus":77},"method","Keyframe-based visual–inertial odometry using nonlinear optimization",[61,62,63,64,65],"Stefan Leutenegger","Simon Lynen","Michael Bosse","Roland Siegwart","Paul Furgale","The International Journal of Robotics Research","journal","SAGE","34(3):314-334","10.1177\u002F0278364914554813",null,"https:\u002F\u002Fspiral.imperial.ac.uk\u002Fhandle\u002F10044\u002F1\u002F23413","2014-12-15","metadata_verified","principle reused: keyframe-based sliding-window nonlinear VIO with marginalisation, explicitly adopted by DSO's windowed optimisation and a common baseline for VINS-Mono.",[11],false,"corrected","author copy","Accepted manuscript deposited in Imperial College Spiral (26 pages); SAGE version of record not compared (journals.sagepub.com returned HTTP 403 to curl)",[82,88,93,98,103,108,113,118],{"category":83,"model":84,"canonical":84,"role":85,"dataset":71,"specs":86,"locator":87},"imu","ADIS16448","method input","MEMS IMU recorded at 800 Hz; noise used: gyro 1.2e-3 rad\u002F(s sqrt(Hz)), accelerometer 8.0e-3 m\u002F(s^2 sqrt(Hz)), gyro bias 2.0e-5, accelerometer bias 5.5e-5 (Table I)","Sec. VII-A1, VII-A2, Table I",{"category":89,"model":90,"canonical":90,"role":85,"dataset":71,"specs":91,"locator":92},"stereo_camera","two embedded WVGA monochrome cameras (model not stated)","11 cm baseline, 20 Hz in the datasets (hardware up to 60 Hz), rigidly mounted on an aluminium frame with the IMU","Sec. VII-A1; Fig. 11",{"category":94,"model":95,"canonical":95,"role":85,"dataset":71,"specs":96,"locator":97},"other","FPGA board of the custom visual-inertial sensor (Nikolic et al. 2014)","hardware synchronisation of imagery and IMU including camera pre-triggering; optional keypoint detection; Gigabit Ethernet to the host","Sec. VII-A1",{"category":99,"model":100,"canonical":100,"role":101,"dataset":71,"specs":102,"locator":97},"compute","host computer (model not stated)","compute for runtime","receives sensor data via Gigabit Ethernet; no specification or timing reported",{"category":94,"model":104,"canonical":104,"role":105,"dataset":71,"specs":106,"locator":107},"Vicon motion tracking system","reference or ground truth","6D ground truth at 200 Hz (Vicon Loops)","Sec. VII-A3, VII-B1; Table II",{"category":109,"model":110,"canonical":110,"role":105,"dataset":71,"specs":111,"locator":112},"gnss","Leica Viva GS14","post-processed DGPS 3D ground truth at 1 Hz; measurements with position uncertainty above 1 m discarded","Sec. VII-A3, VII-B2; Table II",{"category":114,"model":115,"canonical":115,"role":85,"dataset":71,"specs":116,"locator":117},"platform","helmet-mounted sensor and GNSS recorder (bicycle ride)","7940 m in 23 min, up to 13.1 m\u002Fs","Sec. VII-B2; Table II; Fig. 14",{"category":114,"model":119,"canonical":119,"role":85,"dataset":71,"specs":120,"locator":121},"hand-held sensor","Vicon Loops 1200 m; ETH Main Building outdoor loop 620 m; qualitative 470 m indoor walk over three floors","Sec. VII-B1, VII-B3; Fig. 1",[],{"totalRows":124,"groupCount":125,"groups":126,"others":1202},165,16,[127,470,692,900],{"slug":128,"group":129,"sourceId":130,"sourceLabel":131,"table":132,"selfRows":133,"metrics":134,"seqs":144,"entrants":207,"cells":218,"outcomes":462,"locators":464,"hardware":465,"wordings":466,"notes":467},"dmvio2022-table-ii","dmvio2022:Table II","dmvio2022","von Stumberg & Cremers, 2022","Table II",29,[135,140],{"label":136,"unit":137,"statistic":138,"alignment":139},"RMSE ATE","m","RMSE","not_reported",{"label":141,"unit":142,"statistic":143,"alignment":139},"avg drift% normalized (RMSE x 100 \u002F length)","%","mean",[145,149,151,153,155,157,159,161,163,165,167,169,171,173,175,177,179,181,183,185,187,189,191,193,195,197,200,202,204],{"dataset":146,"sequence":147,"environment":148},"TUM-VI","corridor1 (305 m)","handheld, TUM-VI (large-scale indoor and outdoor scenes; the scene of each sequence is not described in this paper)",{"dataset":146,"sequence":150,"environment":148},"corridor2 (322 m)",{"dataset":146,"sequence":152,"environment":148},"corridor3 (300 m)",{"dataset":146,"sequence":154,"environment":148},"corridor4 (114 m)",{"dataset":146,"sequence":156,"environment":148},"corridor5 (270 m)",{"dataset":146,"sequence":158,"environment":148},"magistrale1 (918 m)",{"dataset":146,"sequence":160,"environment":148},"magistrale2 (561 m)",{"dataset":146,"sequence":162,"environment":148},"magistrale3 (566 m)",{"dataset":146,"sequence":164,"environment":148},"magistrale4 (688 m)",{"dataset":146,"sequence":166,"environment":148},"magistrale5 (458 m)",{"dataset":146,"sequence":168,"environment":148},"magistrale6 (771 m)",{"dataset":146,"sequence":170,"environment":148},"outdoors1 (2656 m)",{"dataset":146,"sequence":172,"environment":148},"outdoors2 (1601 m)",{"dataset":146,"sequence":174,"environment":148},"outdoors3 (1531 m)",{"dataset":146,"sequence":176,"environment":148},"outdoors4 (928 m)",{"dataset":146,"sequence":178,"environment":148},"outdoors5 (1168 m)",{"dataset":146,"sequence":180,"environment":148},"outdoors6 (2045 m)",{"dataset":146,"sequence":182,"environment":148},"outdoors7 (1748 m)",{"dataset":146,"sequence":184,"environment":148},"outdoors8 (986 m)",{"dataset":146,"sequence":186,"environment":148},"room1 (146 m)",{"dataset":146,"sequence":188,"environment":148},"room2 (142 m)",{"dataset":146,"sequence":190,"environment":148},"room3 (135 m)",{"dataset":146,"sequence":192,"environment":148},"room4 (68 m)",{"dataset":146,"sequence":194,"environment":148},"room5 (131 m)",{"dataset":146,"sequence":196,"environment":148},"room6 (67 m)",{"dataset":146,"sequence":198,"environment":199},"slides1 (289 m)","handheld, TUM-VI sequences sliding down a tube",{"dataset":146,"sequence":201,"environment":199},"slides2 (299 m)",{"dataset":146,"sequence":203,"environment":199},"slides3 (383 m)",{"dataset":146,"sequence":205,"environment":206},"average over all sequences","handheld indoor and outdoor",[208,210,214,216],{"name":209,"methodId":71,"linkable":77,"proposed":77,"self":77},"ROVIO (stereo)",{"name":211,"methodId":212,"linkable":213,"proposed":77,"self":77},"VINS (VINS-Mono, mono)","vinsmono2018",true,{"name":215,"methodId":5,"linkable":213,"proposed":77,"self":213},"OKVIS (stereo)",{"name":217,"methodId":71,"linkable":77,"proposed":77,"self":77},"BASALT (stereo)",[219,223,226,229,232,234,236,237,239,241,243,245,247,249,251,253,255,258,260,262,264,267,269,271,273,276,278,280,282,285,287,289,291,294,296,297,299,302,303,305,307,309,311,313,315,318,320,321,323,326,328,330,332,335,337,339,341,343,345,347,349,352,354,356,358,360,362,364,366,369,371,373,375,378,380,382,384,387,389,391,393,395,396,398,399,402,403,404,405,407,409,411,413,416,418,419,420,422,424,425,427,430,432,434,436,439,441,443,444,447,449,451,453,456,458,460],[220,220,220,221,222,220,222,222,220],0,0.47,-1,[224,220,220,225,222,220,222,222,220],1,0.63,[227,220,220,228,222,220,222,222,220],2,0.33,[230,220,220,231,222,220,222,222,220],3,0.34,[220,220,224,233,222,220,222,222,220],0.75,[224,220,224,235,222,220,222,222,220],0.95,[227,220,224,221,222,220,222,222,220],[230,220,224,238,222,220,222,222,220],0.42,[220,220,227,240,222,220,222,222,220],0.85,[224,220,227,242,222,220,222,222,220],1.56,[227,220,227,244,222,220,222,222,220],0.57,[230,220,227,246,222,220,222,222,220],0.35,[220,220,230,248,222,220,222,222,220],0.13,[224,220,230,250,222,220,222,222,220],0.25,[227,220,230,252,222,220,222,222,220],0.26,[230,220,230,254,222,220,222,222,220],0.21,[220,220,256,257,222,220,222,222,220],4,2.09,[224,220,256,259,222,220,222,222,220],0.77,[227,220,256,261,222,220,222,222,220],0.39,[230,220,256,263,222,220,222,222,220],0.37,[220,220,265,266,222,220,222,222,220],5,4.52,[224,220,265,268,222,220,222,222,220],2.19,[227,220,265,270,222,220,222,222,220],3.49,[230,220,265,272,222,220,222,222,220],1.2,[220,220,274,275,222,220,222,222,220],6,13.43,[224,220,274,277,222,220,222,222,220],3.11,[227,220,274,279,222,220,222,222,220],2.73,[230,220,274,281,222,220,222,222,220],1.11,[220,220,283,284,222,220,222,222,220],7,14.8,[224,220,283,286,222,220,222,222,220],0.4,[227,220,283,288,222,220,222,222,220],1.22,[230,220,283,290,222,220,222,222,220],0.74,[220,220,292,293,222,220,222,222,220],8,39.73,[224,220,292,295,222,220,222,222,220],5.12,[227,220,292,259,222,220,222,222,220],[230,220,292,298,222,220,222,222,220],1.58,[220,220,300,301,222,220,222,222,220],9,3.47,[224,220,300,240,222,220,222,222,220],[227,220,300,304,222,220,222,222,220],1.62,[230,220,300,306,222,220,222,222,220],0.6,[220,220,308,71,220,220,222,222,220],10,[224,220,308,310,222,220,222,222,220],2.29,[227,220,308,312,222,220,222,222,220],3.91,[230,220,308,314,222,220,222,222,220],3.23,[220,220,316,317,222,220,222,222,220],11,101.95,[224,220,316,319,222,220,222,222,220],74.96,[227,220,316,71,220,220,222,222,220],[230,220,316,322,222,220,222,222,220],255.04,[220,220,324,325,222,220,222,222,220],12,21.67,[224,220,324,327,222,220,222,222,220],133.46,[227,220,324,329,222,220,222,222,220],73.86,[230,220,324,331,222,220,222,222,220],64.61,[220,220,333,334,222,220,222,222,220],13,26.1,[224,220,333,336,222,220,222,222,220],36.99,[227,220,333,338,222,220,222,222,220],32.38,[230,220,333,340,222,220,222,222,220],38.26,[220,220,342,71,220,220,222,222,220],14,[224,220,342,344,222,220,222,222,220],16.46,[227,220,342,346,222,220,222,222,220],19.51,[230,220,342,348,222,220,222,222,220],17.53,[220,220,350,351,222,220,222,222,220],15,54.32,[224,220,350,353,222,220,222,222,220],130.63,[227,220,350,355,222,220,222,222,220],13.12,[230,220,350,357,222,220,222,222,220],7.89,[220,220,125,359,222,220,222,222,220],149.14,[224,220,125,361,222,220,222,222,220],133.6,[227,220,125,363,222,220,222,222,220],96.51,[230,220,125,365,222,220,222,222,220],65.5,[220,220,367,368,222,220,222,222,220],17,49.01,[224,220,367,370,222,220,222,222,220],21.9,[227,220,367,372,222,220,222,222,220],13.61,[230,220,367,374,222,220,222,222,220],4.07,[220,220,376,377,222,220,222,222,220],18,36.03,[224,220,376,379,222,220,222,222,220],83.36,[227,220,376,381,222,220,222,222,220],16.31,[230,220,376,383,222,220,222,222,220],13.53,[220,220,385,386,222,220,222,222,220],19,0.16,[224,220,385,388,222,220,222,222,220],0.07,[227,220,385,390,222,220,222,222,220],0.06,[230,220,385,392,222,220,222,222,220],0.09,[220,220,394,228,222,220,222,222,220],20,[224,220,394,388,222,220,222,222,220],[227,220,394,397,222,220,222,222,220],0.11,[230,220,394,388,222,220,222,222,220],[220,220,400,401,222,220,222,222,220],21,0.15,[224,220,400,397,222,220,222,222,220],[227,220,400,388,222,220,222,222,220],[230,220,400,248,222,220,222,222,220],[220,220,406,392,222,220,222,222,220],22,[224,220,406,408,222,220,222,222,220],0.04,[227,220,406,410,222,220,222,222,220],0.03,[230,220,406,412,222,220,222,222,220],0.05,[220,220,414,415,222,220,222,222,220],23,0.12,[224,220,414,417,222,220,222,222,220],0.2,[227,220,414,388,222,220,222,222,220],[230,220,414,248,222,220,222,222,220],[220,220,421,412,222,220,222,222,220],24,[224,220,421,423,222,220,222,222,220],0.08,[227,220,421,408,222,220,222,222,220],[230,220,421,426,222,220,222,222,220],0.02,[220,220,428,429,222,220,222,222,220],25,13.73,[224,220,428,431,222,220,222,222,220],0.68,[227,220,428,433,222,220,222,222,220],0.86,[230,220,428,435,222,220,222,222,220],0.32,[220,220,437,438,222,220,222,222,220],26,0.81,[224,220,437,440,222,220,222,222,220],0.84,[227,220,437,442,222,220,222,222,220],2.15,[230,220,437,435,222,220,222,222,220],[220,220,445,446,222,220,222,222,220],27,4.68,[224,220,445,448,222,220,222,222,220],0.69,[227,220,445,450,222,220,222,222,220],2.58,[230,220,445,452,222,220,222,222,220],0.89,[220,224,454,455,222,220,222,222,224],28,16.83,[224,224,454,457,222,220,222,222,224],1.7,[227,224,454,459,222,220,222,222,224],0.815,[230,224,454,461,222,220,222,222,224],0.939,[463],"failed",[132],[],[],[468,469],"TUM-VI (handheld); RMSE ATE in m; other methods from the TUM-VI paper, DM-VIO median of 5 runs with SE(3) alignment; X = failure; sequence length in brackets","TUM-VI (handheld); RMSE ATE in m; other methods from the TUM-VI paper, DM-VIO median of 5 runs with SE(3) alignment; X = failure; sequence length in brackets; asterisk on ROVIO and OKVIS averages is not explained in the text (probably failed sequences)",{"slug":471,"group":472,"sourceId":473,"sourceLabel":474,"table":132,"selfRows":406,"metrics":475,"seqs":481,"entrants":506,"cells":515,"outcomes":686,"locators":687,"hardware":688,"wordings":689,"notes":690},"eckenhoff2019closedform-table-ii","eckenhoff2019closedform:Table II","eckenhoff2019closedform","Eckenhoff et al., 2019",[476,478],{"label":477,"unit":137,"statistic":138,"alignment":42},"position RMSE",{"label":479,"unit":480,"statistic":138,"alignment":42},"orientation RMSE","deg",[482,486,488,490,492,494,496,498,500,502,504],{"dataset":483,"sequence":484,"environment":485},"EuRoC MAV","V1 01 easy","public benchmark (EuRoC MAV)",{"dataset":483,"sequence":487,"environment":485},"V1 02 med",{"dataset":483,"sequence":489,"environment":485},"V1 03 diff",{"dataset":483,"sequence":491,"environment":485},"V2 01 easy",{"dataset":483,"sequence":493,"environment":485},"V2 02 med",{"dataset":483,"sequence":495,"environment":485},"V2 03 diff",{"dataset":483,"sequence":497,"environment":485},"MH 01 easy",{"dataset":483,"sequence":499,"environment":485},"MH 02 easy",{"dataset":483,"sequence":501,"environment":485},"MH 03 med",{"dataset":483,"sequence":503,"environment":485},"MH 04 diff",{"dataset":483,"sequence":505,"environment":485},"MH 05 diff",[507,509,511,514],{"name":508,"methodId":473,"linkable":213,"proposed":213,"self":77},"MODEL-1",{"name":510,"methodId":473,"linkable":213,"proposed":213,"self":77},"MODEL-2",{"name":512,"methodId":513,"linkable":213,"proposed":77,"self":77},"DISCRETE","forster2017preint",{"name":7,"methodId":5,"linkable":213,"proposed":77,"self":213},[516,518,520,522,524,526,528,530,532,534,536,538,540,542,544,546,548,550,552,554,556,558,560,562,564,566,568,570,572,573,575,577,579,581,583,585,587,589,591,593,595,597,599,601,603,605,607,609,611,613,615,617,619,621,623,625,627,629,631,633,635,637,639,640,641,643,645,647,649,650,651,653,655,657,659,661,663,665,667,669,671,673,675,677,679,681,682,684],[220,220,220,517,222,220,222,222,220],0.2522,[220,224,220,519,222,220,222,222,220],2.749,[224,220,220,521,222,220,222,222,220],0.216,[224,224,220,523,222,220,222,222,220],2.503,[227,220,220,525,222,220,222,222,220],0.2547,[227,224,220,527,222,220,222,222,220],2.781,[230,220,220,529,222,220,222,222,220],0.2356,[230,224,220,531,222,220,222,222,220],2.458,[220,220,224,533,222,220,222,222,220],0.1342,[220,224,224,535,222,220,222,222,220],0.942,[224,220,224,537,222,220,222,222,220],0.1214,[224,224,224,539,222,220,222,222,220],1.215,[227,220,224,541,222,220,222,222,220],0.1344,[227,224,224,543,222,220,222,222,220],1.001,[230,220,224,545,222,220,222,222,220],0.1996,[230,224,224,547,222,220,222,222,220],2.321,[220,220,227,549,222,220,222,222,220],0.1101,[220,224,227,551,222,220,222,222,220],0.88,[224,220,227,553,222,220,222,222,220],0.0953,[224,224,227,555,222,220,222,222,220],0.809,[227,220,227,557,222,220,222,222,220],0.1012,[227,224,227,559,222,220,222,222,220],0.83,[230,220,227,561,222,220,222,222,220],0.183,[230,224,227,563,222,220,222,222,220],3.498,[220,220,230,565,222,220,222,222,220],0.1429,[220,224,230,567,222,220,222,222,220],1.069,[224,220,230,569,222,220,222,222,220],0.1426,[224,224,230,571,222,220,222,222,220],1.148,[227,220,230,569,222,220,222,222,220],[227,224,230,574,222,220,222,222,220],1.118,[230,220,230,576,222,220,222,222,220],0.1806,[230,224,230,578,222,220,222,222,220],0.973,[220,220,256,580,222,220,222,222,220],0.1297,[220,224,256,582,222,220,222,222,220],1.39,[224,220,256,584,222,220,222,222,220],0.1223,[224,224,256,586,222,220,222,222,220],1.135,[227,220,256,588,222,220,222,222,220],0.1375,[227,224,256,590,222,220,222,222,220],1.45,[230,220,256,592,222,220,222,222,220],0.1695,[230,224,256,594,222,220,222,222,220],2.334,[220,220,265,596,222,220,222,222,220],0.2982,[220,224,265,598,222,220,222,222,220],2.159,[224,220,265,600,222,220,222,222,220],0.28,[224,224,265,602,222,220,222,222,220],1.769,[227,220,265,604,222,220,222,222,220],0.3055,[227,224,265,606,222,220,222,222,220],2.052,[230,220,265,608,222,220,222,222,220],0.3483,[230,224,265,610,222,220,222,222,220],8.327,[220,220,274,612,222,220,222,222,220],0.1817,[220,224,274,614,222,220,222,222,220],1.398,[224,220,274,616,222,220,222,222,220],0.1653,[224,224,274,618,222,220,222,222,220],1.761,[227,220,274,620,222,220,222,222,220],0.205,[227,224,274,622,222,220,222,222,220],1.321,[230,220,274,624,222,220,222,222,220],0.2523,[230,224,274,626,222,220,222,222,220],0.728,[220,220,283,628,222,220,222,222,220],0.1533,[220,224,283,630,222,220,222,222,220],0.691,[224,220,283,632,222,220,222,222,220],0.1498,[224,224,283,634,222,220,222,222,220],0.525,[227,220,283,636,222,220,222,222,220],0.1564,[227,224,283,638,222,220,222,222,220],0.599,[230,220,283,624,222,220,222,222,220],[230,224,283,626,222,220,222,222,220],[220,220,292,642,222,220,222,222,220],0.2993,[220,224,292,644,222,220,222,222,220],1.024,[224,220,292,646,222,220,222,222,220],0.2627,[224,224,292,648,222,220,222,222,220],0.968,[227,220,292,600,222,220,222,222,220],[227,224,292,440,222,220,222,222,220],[230,220,292,652,222,220,222,222,220],0.3193,[230,224,292,654,222,220,222,222,220],1.903,[220,220,300,656,222,220,222,222,220],0.3312,[220,224,300,658,222,220,222,222,220],0.849,[224,220,300,660,222,220,222,222,220],0.3515,[224,224,300,662,222,220,222,222,220],0.974,[227,220,300,664,222,220,222,222,220],0.3488,[227,224,300,666,222,220,222,222,220],0.852,[230,220,300,668,222,220,222,222,220],0.2145,[230,224,300,670,222,220,222,222,220],1.022,[220,220,308,672,222,220,222,222,220],0.3939,[220,224,308,674,222,220,222,222,220],0.692,[224,220,308,676,222,220,222,222,220],0.3971,[224,224,308,678,222,220,222,222,220],0.715,[227,220,308,680,222,220,222,222,220],0.3835,[227,224,308,555,222,220,222,222,220],[230,220,308,683,222,220,222,222,220],0.5432,[230,224,308,685,222,220,222,222,220],0.738,[],[132],[],[],[691],"Indirect stereo VIO; absolute RMSE averaged over 10 runs; ground-truth initialisation",{"slug":693,"group":694,"sourceId":695,"sourceLabel":696,"table":697,"selfRows":394,"metrics":698,"seqs":701,"entrants":723,"cells":751,"outcomes":894,"locators":895,"hardware":896,"wordings":897,"notes":898},"basalt2020-table-i","basalt2020:Table I","basalt2020","Usenko et al., 2020","Table I",[699],{"label":700,"unit":137,"statistic":138,"alignment":139},"RMS ATE of the estimated trajectory",[702,705,707,709,711,713,715,717,719,721],{"dataset":483,"sequence":703,"environment":704},"MH_01","indoor MAV (machine hall and Vicon room)",{"dataset":483,"sequence":706,"environment":704},"MH_02",{"dataset":483,"sequence":708,"environment":704},"MH_03",{"dataset":483,"sequence":710,"environment":704},"MH_04",{"dataset":483,"sequence":712,"environment":704},"MH_05",{"dataset":483,"sequence":714,"environment":704},"V1_01",{"dataset":483,"sequence":716,"environment":704},"V1_02",{"dataset":483,"sequence":718,"environment":704},"V1_03",{"dataset":483,"sequence":720,"environment":704},"V2_01",{"dataset":483,"sequence":722,"environment":704},"V2_02",[724,726,728,730,733,735,737,739,741,743,745,747,749],{"name":725,"methodId":71,"linkable":77,"proposed":77,"self":77},"VI DSO, mono",{"name":727,"methodId":5,"linkable":213,"proposed":77,"self":213},"OKVIS mono",{"name":729,"methodId":5,"linkable":213,"proposed":77,"self":213},"OKVIS stereo",{"name":731,"methodId":732,"linkable":213,"proposed":77,"self":77},"VINS FUSION mono","vinsfusion2019",{"name":734,"methodId":732,"linkable":213,"proposed":77,"self":77},"VINS FUSION stereo",{"name":736,"methodId":71,"linkable":77,"proposed":77,"self":77},"IS VIO stereo",{"name":738,"methodId":71,"linkable":77,"proposed":213,"self":77},"Proposed VIO, stereo",{"name":740,"methodId":71,"linkable":77,"proposed":77,"self":77},"VI SLAM (Kasyanov et al.) mono, KF",{"name":742,"methodId":71,"linkable":77,"proposed":77,"self":77},"VI SLAM (Kasyanov et al.) stereo, KF",{"name":744,"methodId":71,"linkable":77,"proposed":77,"self":77},"VI ORB-SLAM mono, KF",{"name":746,"methodId":71,"linkable":77,"proposed":77,"self":77},"Pure BA, stereo, KF (ablation)",{"name":748,"methodId":71,"linkable":77,"proposed":77,"self":77},"BA + Identity Factors, stereo, KF (ablation)",{"name":750,"methodId":71,"linkable":77,"proposed":213,"self":77},"Proposed VI Mapping, stereo, KF",[752,753,754,756,758,760,761,762,763,764,765,766,767,768,769,771,772,773,774,775,776,777,778,779,780,781,782,783,785,786,788,789,791,792,793,795,796,797,798,799,800,802,803,804,805,806,807,808,810,812,813,814,815,816,817,818,819,820,821,822,823,824,825,826,827,828,829,830,831,832,833,834,835,836,837,838,839,840,841,842,843,844,845,846,847,848,849,850,851,852,853,854,855,856,857,858,859,860,861,862,863,864,865,867,868,869,870,871,872,873,874,875,876,877,878,879,880,881,882,883,884,885,886,887,888,889,890,891,892,893],[220,220,220,390,222,220,222,222,220],[224,220,220,231,222,220,222,222,220],[227,220,220,755,222,220,222,222,220],0.23,[230,220,220,757,222,220,222,222,220],0.18,[256,220,220,759,222,220,222,222,220],0.24,[265,220,220,390,222,220,222,222,220],[274,220,220,388,222,220,222,222,220],[283,220,220,250,222,220,222,222,220],[292,220,220,397,222,220,222,222,220],[300,220,220,388,222,220,222,222,220],[308,220,220,392,222,220,222,222,220],[316,220,220,423,222,220,222,222,220],[324,220,220,423,222,220,222,222,220],[220,220,224,408,222,220,222,222,220],[224,220,224,770,222,220,222,222,220],0.36,[227,220,224,401,222,220,222,222,220],[230,220,224,392,222,220,222,222,220],[256,220,224,757,222,220,222,222,220],[265,220,224,390,222,220,222,222,220],[274,220,224,390,222,220,222,222,220],[283,220,224,757,222,220,222,222,220],[292,220,224,392,222,220,222,222,220],[300,220,224,423,222,220,222,222,220],[308,220,224,423,222,220,222,222,220],[316,220,224,388,222,220,222,222,220],[324,220,224,390,222,220,222,222,220],[220,220,227,415,222,220,222,222,220],[224,220,227,784,222,220,222,222,220],0.3,[227,220,227,755,222,220,222,222,220],[230,220,227,787,222,220,222,222,220],0.17,[256,220,227,755,222,220,222,222,220],[265,220,227,790,222,220,222,222,220],0.1,[274,220,227,388,222,220,222,222,220],[283,220,227,254,222,220,222,222,220],[292,220,227,794,222,220,222,222,220],0.19,[300,220,227,392,222,220,222,222,220],[308,220,227,412,222,220,222,222,220],[316,220,227,71,220,220,222,222,220],[324,220,227,412,222,220,222,222,220],[220,220,230,248,222,220,222,222,220],[224,220,230,801,222,220,222,222,220],0.48,[227,220,230,435,222,220,222,222,220],[230,220,230,254,222,220,222,222,220],[256,220,230,261,222,220,222,222,220],[265,220,230,759,222,220,222,222,220],[274,220,230,248,222,220,222,222,220],[283,220,230,784,222,220,222,222,220],[292,220,230,809,222,220,222,222,220],0.27,[300,220,230,811,222,220,222,222,220],0.22,[308,220,230,809,222,220,222,222,220],[316,220,230,231,222,220,222,222,220],[324,220,230,790,222,220,222,222,220],[220,220,256,415,222,220,222,222,220],[224,220,256,221,222,220,222,222,220],[227,220,256,770,222,220,222,222,220],[230,220,256,250,222,220,222,222,220],[256,220,256,794,222,220,222,222,220],[265,220,256,794,222,220,222,222,220],[274,220,256,397,222,220,222,222,220],[283,220,256,246,222,220,222,222,220],[292,220,256,755,222,220,222,222,220],[300,220,256,423,222,220,222,222,220],[308,220,256,386,222,220,222,222,220],[316,220,256,401,222,220,222,222,220],[324,220,256,423,222,220,222,222,220],[220,220,265,390,222,220,222,222,220],[224,220,265,415,222,220,222,222,220],[227,220,265,408,222,220,222,222,220],[230,220,265,390,222,220,222,222,220],[256,220,265,790,222,220,222,222,220],[265,220,265,390,222,220,222,222,220],[274,220,265,408,222,220,222,222,220],[283,220,265,397,222,220,222,222,220],[292,220,265,408,222,220,222,222,220],[300,220,265,410,222,220,222,222,220],[308,220,265,408,222,220,222,222,220],[316,220,265,408,222,220,222,222,220],[324,220,265,408,222,220,222,222,220],[220,220,274,388,222,220,222,222,220],[224,220,274,386,222,220,222,222,220],[227,220,274,423,222,220,222,222,220],[230,220,274,392,222,220,222,222,220],[256,220,274,790,222,220,222,222,220],[265,220,274,790,222,220,222,222,220],[274,220,274,412,222,220,222,222,220],[283,220,274,248,222,220,222,222,220],[292,220,274,412,222,220,222,222,220],[300,220,274,410,222,220,222,222,220],[308,220,274,410,222,220,222,222,220],[316,220,274,410,222,220,222,222,220],[324,220,274,426,222,220,222,222,220],[220,220,283,790,222,220,222,222,220],[224,220,283,759,222,220,222,222,220],[227,220,283,248,222,220,222,222,220],[230,220,283,757,222,220,222,222,220],[256,220,283,397,222,220,222,222,220],[265,220,283,252,222,220,222,222,220],[274,220,283,790,222,220,222,222,220],[283,220,283,417,222,220,222,222,220],[292,220,283,397,222,220,222,222,220],[300,220,283,71,220,220,222,222,220],[308,220,283,71,220,220,222,222,220],[316,220,283,866,222,220,222,222,220],0.56,[324,220,283,410,222,220,222,222,220],[220,220,292,408,222,220,222,222,220],[224,220,292,415,222,220,222,222,220],[227,220,292,790,222,220,222,222,220],[230,220,292,390,222,220,222,222,220],[256,220,292,415,222,220,222,222,220],[265,220,292,423,222,220,222,222,220],[274,220,292,408,222,220,222,222,220],[283,220,292,415,222,220,222,222,220],[292,220,292,790,222,220,222,222,220],[300,220,292,410,222,220,222,222,220],[308,220,292,408,222,220,222,222,220],[316,220,292,412,222,220,222,222,220],[324,220,292,410,222,220,222,222,220],[220,220,300,390,222,220,222,222,220],[224,220,300,811,222,220,222,222,220],[227,220,300,787,222,220,222,222,220],[230,220,300,397,222,220,222,222,220],[256,220,300,790,222,220,222,222,220],[265,220,300,254,222,220,222,222,220],[274,220,300,412,222,220,222,222,220],[283,220,300,417,222,220,222,222,220],[292,220,300,757,222,220,222,222,220],[300,220,300,408,222,220,222,222,220],[308,220,300,408,222,220,222,222,220],[316,220,300,408,222,220,222,222,220],[324,220,300,426,222,220,222,222,220],[463],[697],[],[],[899],"EuRoC MAV; RMS ATE (m) after alignment with ground truth; upper part VIO methods (pose per frame), lower part mapping methods on keyframes (KF); X = failure; V2_03 excluded",{"slug":901,"group":902,"sourceId":903,"sourceLabel":904,"table":132,"selfRows":394,"metrics":905,"seqs":910,"entrants":922,"cells":949,"outcomes":1196,"locators":1197,"hardware":1198,"wordings":1199,"notes":1200},"openvins2020-table-ii","openvins2020:Table II","openvins2020","Geneva et al., 2020",[906,908],{"label":907,"unit":137,"statistic":143,"alignment":139},"ATE position (m), mean of ten runs",{"label":909,"unit":480,"statistic":143,"alignment":139},"ATE orientation (deg), mean of ten runs",[911,914,916,918,920],{"dataset":483,"sequence":912,"environment":913},"V1_01_easy","indoor Vicon room, MAV",{"dataset":483,"sequence":915,"environment":913},"V1_02_medium",{"dataset":483,"sequence":917,"environment":913},"V1_03_difficult",{"dataset":483,"sequence":919,"environment":913},"V2_01_easy",{"dataset":483,"sequence":921,"environment":913},"V2_02_medium",[923,925,927,929,931,933,935,937,939,941,943,945,947],{"name":924,"methodId":71,"linkable":77,"proposed":213,"self":77},"mono ov slam",{"name":926,"methodId":71,"linkable":77,"proposed":213,"self":77},"mono ov vio",{"name":928,"methodId":5,"linkable":213,"proposed":77,"self":213},"mono okvis",{"name":930,"methodId":71,"linkable":77,"proposed":77,"self":77},"mono rovioli (ROVIO in maplab)",{"name":932,"methodId":71,"linkable":77,"proposed":77,"self":77},"mono rvio (R-VIO)",{"name":934,"methodId":732,"linkable":213,"proposed":77,"self":77},"mono vinsfusion vio",{"name":936,"methodId":71,"linkable":77,"proposed":213,"self":77},"stereo ov slam",{"name":938,"methodId":71,"linkable":77,"proposed":213,"self":77},"stereo ov vio",{"name":940,"methodId":71,"linkable":77,"proposed":77,"self":77},"stereo basalt (VIO)",{"name":942,"methodId":71,"linkable":77,"proposed":77,"self":77},"stereo iceba (ICE-BA)",{"name":944,"methodId":5,"linkable":213,"proposed":77,"self":213},"stereo okvis",{"name":946,"methodId":71,"linkable":77,"proposed":77,"self":77},"stereo smsckf (S-MSCKF)",{"name":948,"methodId":732,"linkable":213,"proposed":77,"self":77},"stereo vinsfusion vio",[950,952,954,955,957,959,961,963,964,966,968,970,972,974,976,978,980,982,984,986,988,990,992,994,996,998,1000,1001,1003,1005,1007,1009,1011,1013,1015,1016,1017,1019,1021,1023,1025,1027,1029,1031,1033,1035,1037,1039,1041,1043,1045,1047,1049,1051,1053,1055,1057,1059,1061,1062,1064,1066,1068,1070,1072,1074,1076,1078,1080,1082,1084,1086,1088,1090,1092,1094,1096,1098,1100,1102,1103,1105,1107,1109,1111,1112,1114,1116,1118,1120,1122,1124,1126,1128,1130,1132,1134,1136,1138,1140,1142,1144,1146,1148,1150,1152,1153,1155,1156,1158,1159,1160,1162,1163,1165,1167,1169,1170,1172,1174,1176,1178,1180,1182,1184,1186,1188,1190,1192,1194],[220,220,220,951,222,220,222,222,220],0.058,[224,220,220,953,222,220,222,222,220],0.076,[227,220,220,392,222,220,222,222,220],[230,220,220,956,222,220,222,222,220],0.153,[256,220,220,958,222,220,222,222,220],0.094,[265,220,220,960,222,220,222,222,220],0.064,[274,220,220,962,222,220,222,222,220],0.061,[283,220,220,962,222,220,222,222,220],[292,220,220,965,222,220,222,222,220],0.035,[300,220,220,967,222,220,222,222,220],0.059,[308,220,220,969,222,220,222,222,220],0.039,[316,220,220,971,222,220,222,222,220],0.086,[324,220,220,973,222,220,222,222,220],0.054,[220,224,220,975,222,220,222,222,220],0.699,[224,224,220,977,222,220,222,222,220],0.642,[227,224,220,979,222,220,222,222,220],0.823,[230,224,220,981,222,220,222,222,220],2.249,[256,224,220,983,222,220,222,222,220],0.994,[265,224,220,985,222,220,222,222,220],1.199,[274,224,220,987,222,220,222,222,220],0.856,[283,224,220,989,222,220,222,222,220],0.905,[292,224,220,991,222,220,222,222,220],0.654,[300,224,220,993,222,220,222,222,220],0.909,[308,224,220,995,222,220,222,222,220],0.603,[316,224,220,997,222,220,222,222,220],1.108,[324,224,220,999,222,220,222,222,220],1.073,[220,220,224,953,222,220,222,222,220],[224,220,224,1002,222,220,222,222,220],0.096,[227,220,224,1004,222,220,222,222,220],0.146,[230,220,224,1006,222,220,222,222,220],0.131,[256,220,224,1008,222,220,222,222,220],0.129,[265,220,224,1010,222,220,222,222,220],0.103,[274,220,224,1012,222,220,222,222,220],0.047,[283,220,224,1014,222,220,222,222,220],0.056,[292,220,224,967,222,220,222,222,220],[300,220,224,415,222,220,222,222,220],[308,220,224,1018,222,220,222,222,220],0.079,[316,220,224,1020,222,220,222,222,220],0.121,[324,220,224,1022,222,220,222,222,220],0.089,[220,224,224,1024,222,220,222,222,220],1.675,[224,224,224,1026,222,220,222,222,220],1.766,[227,224,224,1028,222,220,222,222,220],2.082,[230,224,224,1030,222,220,222,222,220],1.635,[256,224,224,1032,222,220,222,222,220],2.288,[265,224,224,1034,222,220,222,222,220],3.542,[274,224,224,1036,222,220,222,222,220],1.813,[283,224,224,1038,222,220,222,222,220],1.767,[292,224,224,1040,222,220,222,222,220],2.067,[300,224,224,1042,222,220,222,222,220],2.574,[308,224,224,1044,222,220,222,222,220],1.963,[316,224,224,1046,222,220,222,222,220],2.147,[324,224,224,1048,222,220,222,222,220],2.695,[220,220,227,1050,222,220,222,222,220],0.063,[224,220,227,1052,222,220,222,222,220],0.344,[227,220,227,1054,222,220,222,222,220],0.222,[230,220,227,1056,222,220,222,222,220],0.158,[256,220,227,1058,222,220,222,222,220],0.147,[265,220,227,1060,222,220,222,222,220],0.202,[274,220,227,967,222,220,222,222,220],[283,220,227,1063,222,220,222,222,220],0.057,[292,220,227,1065,222,220,222,222,220],0.085,[300,220,227,1067,222,220,222,222,220],0.137,[308,220,227,1069,222,220,222,222,220],0.122,[316,220,227,1071,222,220,222,222,220],0.198,[324,220,227,1073,222,220,222,222,220],0.132,[220,224,227,1075,222,220,222,222,220],2.542,[224,224,227,1077,222,220,222,222,220],2.391,[227,224,227,1079,222,220,222,222,220],4.122,[230,224,227,1081,222,220,222,222,220],3.253,[256,224,227,1083,222,220,222,222,220],1.757,[265,224,227,1085,222,220,222,222,220],5.934,[274,224,227,1087,222,220,222,222,220],2.764,[283,224,227,1089,222,220,222,222,220],2.339,[292,224,227,1091,222,220,222,222,220],2.017,[300,224,227,1093,222,220,222,222,220],3.206,[308,224,227,1095,222,220,222,222,220],4.117,[316,224,227,1097,222,220,222,222,220],3.918,[324,224,227,1099,222,220,222,222,220],3.643,[220,220,230,1101,222,220,222,222,220],0.124,[224,220,230,1020,222,220,222,222,220],[227,220,230,1104,222,220,222,222,220],0.117,[230,220,230,1106,222,220,222,222,220],0.106,[256,220,230,1108,222,220,222,222,220],0.144,[265,220,230,1110,222,220,222,222,220],0.073,[274,220,230,1014,222,220,222,222,220],[283,220,230,1113,222,220,222,222,220],0.053,[292,220,230,1115,222,220,222,222,220],0.046,[300,220,230,1117,222,220,222,222,220],0.128,[308,220,230,1119,222,220,222,222,220],0.075,[316,220,230,1121,222,220,222,222,220],0.083,[324,220,230,1123,222,220,222,222,220],0.071,[220,224,230,1125,222,220,222,222,220],0.773,[224,224,230,1127,222,220,222,222,220],1.164,[227,224,230,1129,222,220,222,222,220],0.826,[230,224,230,1131,222,220,222,222,220],1.455,[256,224,230,1133,222,220,222,222,220],1.735,[265,224,230,1135,222,220,222,222,220],1.585,[274,224,230,1137,222,220,222,222,220],1.037,[283,224,230,1139,222,220,222,222,220],1.106,[292,224,230,1141,222,220,222,222,220],0.981,[300,224,230,1143,222,220,222,222,220],1.819,[308,224,230,1145,222,220,222,222,220],0.834,[316,224,230,1147,222,220,222,222,220],1.181,[324,224,230,1149,222,220,222,222,220],2.499,[220,220,256,1151,222,220,222,222,220],0.074,[224,220,256,1106,222,220,222,222,220],[227,220,256,1154,222,220,222,222,220],0.197,[230,220,256,956,222,220,222,222,220],[256,220,256,1157,222,220,222,222,220],0.233,[265,220,256,1018,222,220,222,222,220],[274,220,256,1012,222,220,222,222,220],[283,220,256,1161,222,220,222,222,220],0.048,[292,220,256,967,222,220,222,222,220],[300,220,256,1164,222,220,222,222,220],0.116,[308,220,256,1166,222,220,222,222,220],0.092,[316,220,256,1168,222,220,222,222,220],0.164,[324,220,256,1151,222,220,222,222,220],[220,224,256,1171,222,220,222,222,220],1.538,[224,224,256,1173,222,220,222,222,220],1.248,[227,224,256,1175,222,220,222,222,220],1.704,[230,224,256,1177,222,220,222,222,220],1.678,[256,224,256,1179,222,220,222,222,220],1.69,[265,224,256,1181,222,220,222,222,220],2.37,[274,224,256,1183,222,220,222,222,220],1.292,[283,224,256,1185,222,220,222,222,220],1.151,[292,224,256,1187,222,220,222,222,220],0.888,[300,224,256,1189,222,220,222,222,220],1.212,[308,224,256,1191,222,220,222,222,220],1.201,[316,224,256,1193,222,220,222,222,220],2.142,[324,224,256,1195,222,220,222,222,220],2.006,[],[132],[],[],[1201],"EuRoC MAV Vicon-room sequences, mean ATE over ten runs per method (orientation deg \u002F position m); VIO outputs only; V2_03 excluded; alignment method not stated",[1203,1209,1215,1220,1225,1230,1236,1242,1246,1252,1258,1265],{"group":1204,"slug":1205,"sourceLabel":1206,"table":1207,"selfRows":324,"datasets":1208},"d3vo2020:Table 6","d3vo2020-table-6","Yang et al., 2020a","Table 6",[483],{"group":1210,"slug":1211,"sourceLabel":1212,"table":132,"selfRows":324,"datasets":1213},"orbslam3_2021:Table II","orbslam3-2021-table-ii","Campos et al., 2021",[1214],"EuRoC",{"group":1216,"slug":1217,"sourceLabel":1218,"table":132,"selfRows":316,"datasets":1219},"kimera2020:Table II","kimera2020-table-ii","Rosinol et al., 2020",[483],{"group":1221,"slug":1222,"sourceLabel":1223,"table":697,"selfRows":316,"datasets":1224},"vinsfusion2019:Table I","vinsfusion2019-table-i","Qin et al., 2019",[1214],{"group":1226,"slug":1227,"sourceLabel":1228,"table":697,"selfRows":316,"datasets":1229},"vinsmono2018:Table I","vinsmono2018-table-i","Qin et al., 2018",[1214],{"group":1231,"slug":1232,"sourceLabel":1233,"table":132,"selfRows":308,"datasets":1234},"maplab2_2023:Table II","maplab2-2023-table-ii","Cramariuc et al., 2023",[1235],"HILTI 2021 SLAM Dataset",{"group":1237,"slug":1238,"sourceLabel":6,"table":1239,"selfRows":227,"datasets":1240},"okvis2015:Text Sec.VII-B1","okvis2015-text-sec-vii-b1","Text Sec.VII-B1",[1241],"Vicon Loops (authors' dataset)",{"group":1243,"slug":1244,"sourceLabel":131,"table":697,"selfRows":224,"datasets":1245},"dmvio2022:Table I","dmvio2022-table-i",[483],{"group":1247,"slug":1248,"sourceLabel":474,"table":1249,"selfRows":224,"datasets":1250},"eckenhoff2019closedform:Text Sec.VII-A2 (Gore Hall)","eckenhoff2019closedform-text-sec-vii-a2-gore-hall","Text Sec.VII-A2 (Gore Hall)",[1251],"UD Gore Hall",{"group":1253,"slug":1254,"sourceLabel":474,"table":1255,"selfRows":224,"datasets":1256},"eckenhoff2019closedform:Text Sec.VII-A2 (Smith Hall)","eckenhoff2019closedform-text-sec-vii-a2-smith-hall","Text Sec.VII-A2 (Smith Hall)",[1257],"UD Smith Hall",{"group":1259,"slug":1260,"sourceLabel":1261,"table":1262,"selfRows":224,"datasets":1263},"forster2017preint:Text Sec.VIII-B2 (drift)","forster2017preint-text-sec-viii-b2-drift","Forster et al., 2017a","Text Sec.VIII-B2 (drift)",[1264],"430 m indoor sequence recorded with a forward-looking VI-Sensor, with Vicon ground truth; dataset and OKVIS and MSCKF trajectories obtained from the OKVIS authors",{"group":1266,"slug":1267,"sourceLabel":1268,"table":1269,"selfRows":224,"datasets":1270},"ghadimzadeh2025slamnde:Table 2","ghadimzadeh2025slamnde-table-2","Ghadimzadeh Alamdari et al., 2025","Table 2",[1271],"Luleå SubT tunnel dataset (Koval et al. 2022)",1790510659246]