[{"data":1,"prerenderedAt":289},["ShallowReactive",2],{"method-lion2021":3},{"method":4,"reference":59,"equipment":85,"figures":113,"results":114},{"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":23,"limitations":29,"sensors":36,"platform":39,"estimator":42,"association":43,"timeModel":44,"deskew":45,"loopClosure":46,"globalOptimization":47,"mapRepresentation":48,"prior":49,"outputGeometry":50,"compute":51,"codeUrl":52,"codeLicense":53,"relatedVersions":54},"lion2021","Tagliabue et al., 2021","LION","LION: Lidar-Inertial Observability-Aware Navigator for Vision-Denied Environments",2021,"recent","C05","odometry","LION 是 CoSTAR 團隊參加 DARPA 地下挑戰賽所用的 LiDAR 慣性里程計。前端以廣義 ICP 做相鄰掃描配準並先以 IMU 旋轉對齊重力，後端在 GTSAM 中以 3 秒固定延遲滑動視窗平滑器融合 IMU 預積分與掃描間相對位姿，同時線上估計 LiDAR 與 IMU 外參；作者明確說明它是鬆耦合架構，且不建地圖、不做迴圈閉合。另以點到平面 ICP Hessian 平移區塊的條件數作為可觀性指標，條件數過大時通知監督邏輯 HeRO 改用其他里程計來源，例如輪式慣性里程計。","Loosely coupled fixed-lag smoother (GTSAM iSAM2, 3 s window) that fuses IMU preintegration with scan-to-scan GICP relative poses, estimates LiDAR-IMU extrinsics online, and reports the condition number of the translational point-to-plane ICP Hessian as an observability score so a supervisor can switch odometry sources in degenerate tunnels.","full_text_reviewed","peer_reviewed_published","background","論文在美國 NIOSH 實驗礦坑、煤礦與金礦等地下環境以及 JPL 辦公室走廊測試，未涉及營建工地，參考軌跡為團隊自己的 LAMP 輸出而非獨立測量。其以 ICP Hessian 平移部分條件數偵測長走廊與隧道退化，並交由監督邏輯切換到輪式慣性里程計的做法，可直接對應施工中隧道與長廊的定位風險管理（推論）。",[20,21,22],"underground_or_tunnel","completed_building","simulation",[24,25,26,27,28],"Fusing IMU with scan-to-scan odometry cut position drift strongly, e.g. Track A Run 2 from 18.72 m (4.11%) to 7.00 m (1.53%) (Table 1)","Position RMSE comparable to LOAM on the shorter runs (Track A Run 2 7.00 vs 7.22 m; Track B Run 2 3.78 vs 5.55 m), with gravity-aligned output at IMU rate rather than LiDAR rate; the authors report comparable or slightly lower roll and pitch errors in Fig. 5 (Sec. 3.1, Table 1)","Online extrinsic calibration recovered a 0.1 m simulated offset within about 20 s (Sec. 3.1, Fig. 7)","Condition number rose above 13 in a featureless corridor and above 10 along a mine shaft, and switching to wheel-inertial odometry reduced a return error from about 9 m to about 1 m (Sec. 3.2, Figs. 8-10)","Uses about 30% of one NUC i7 core (Sec. 3.1)",[30,31,32,33,34,35],"No map and no loop closure; the odometry frame drifts slowly and relies on LAMP for correction (Sec. 4)","LOAM achieved lower position and yaw drift on longer trajectories thanks to its map, e.g. 10.99 m versus 56.92 m on Track A Run 1 (Sec. 3.1, Table 1)","Attitude RMSE in Table 1 is higher than LOAM on all four runs (0.36, 0.10, 0.27, 0.05 rad versus 0.14, 0.08, 0.21, 0.03 rad) (Table 1)","Loosely coupled design chosen for shared compute and modularity rather than accuracy (Sec. 4)","Reference trajectories come from the team's own LAMP SLAM system, not an independent survey (Sec. 3.1)","Observability threshold is user defined (Sec. 2)",[37,38],"3D LiDAR (model not named)","IMU (model not named)",[40,41],"wheeled UGV (team CoSTAR ground robots in mines and offices)","simulation (extrinsic calibration test)","fixed-lag sliding-window smoother (3 s window) in GTSAM solved with iSAM2, fusing IMU preintegration factors with relative-pose factors from LiDAR odometry; loosely coupled because points or scans are not in the state (Sec. 2, 3.1, 4)","scan-to-scan Generalized ICP between consecutive clouds, each pre-rotated into a gravity-aligned frame with the IMU rotation as initial guess; no feature extraction; LOCUS can replace the front-end (Sec. 2, 4)","discrete poses in a sliding window with IMU preintegration (Sec. 2)","not_reported","none within LION; drift is compensated by the separate LAMP mapping system (Sec. 4)","none within LION","none (LION builds no map) (Sec. 4)","none; LiDAR-IMU extrinsics (rotation and translation) estimated online in the state (Sec. 2)","gravity-aligned odometry at up to 200 Hz plus an observability (condition-number) score for a supervisory switching logic (HeRO) (Sec. 2, 3.1)","back-end tuned to use about 30% of one CPU core of an Intel i7 NUC; LiDAR odometry at 10 Hz, output up to 200 Hz (Sec. 3.1)",null,"not_applicable (no public code found)",[55],{"relation":56,"title":57,"doi_or_url":58},"preprint","arXiv 2102.03443 v1 (2021-02-05), only version","https:\u002F\u002Farxiv.org\u002Fabs\u002F2102.03443",{"id":5,"kind":60,"shortName":7,"title":8,"authors":61,"year":9,"venue":69,"venueType":70,"publisher":71,"volumeIssuePages":72,"doi":73,"arxivId":74,"url":75,"firstPublicDate":76,"publicationStatus":16,"metadataStatus":77,"fulltextStatus":15,"era":10,"classicReason":78,"codeUrl":52,"cluster":11,"topics":79,"mdpi":80,"verification":81,"label":6,"fulltextRoute":82,"versionRead":83,"addedByCensus":84},"method",[62,63,64,65,66,67,68],"Andrea Tagliabue","Jesus Tordesillas","Xiaoyi Cai","Angel Santamaria-Navarro","Jonathan P. How","Luca Carlone","Ali-akbar Agha-mohammadi","Experimental Robotics (ISER 2020), Springer Proceedings in Advanced Robotics 19","conference","Springer","SPAR 19, pp. 380-390","10.1007\u002F978-3-030-71151-1_34","2102.03443","https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-030-71151-1_34","2021-02-05","metadata_verified","not_applicable",[11],false,"corrected","NTU institutional (curl)","Springer version of record (SPAR 19, pp. 380-390, 2021)",true,[86,92,98,103,107],{"category":87,"model":88,"canonical":88,"role":89,"dataset":52,"specs":90,"locator":91},"platform","team CoSTAR ground robots (not further specified)","method input","explored the Arch Coal Mine about 275 m underground","Fig. 1; Sec. 1",{"category":93,"model":94,"canonical":94,"role":95,"dataset":52,"specs":96,"locator":97},"compute","Intel NUC with i7 processor (model not stated)","compute for runtime","LION back-end used about 30% of one CPU core","Sec. 3.1",{"category":99,"model":100,"canonical":100,"role":89,"dataset":52,"specs":101,"locator":102},"lidar","3D LiDAR (model not stated)","LiDAR odometry computed at 10 Hz","Sec. 2; Sec. 3.1",{"category":104,"model":105,"canonical":105,"role":89,"dataset":52,"specs":106,"locator":102},"imu","IMU (model not stated)","IMU and LION output provided at up to 200 Hz",{"category":108,"model":109,"canonical":109,"role":110,"dataset":52,"specs":111,"locator":112},"wheel_or_leg_odometry","wheel odometry (encoders, model not stated)","compared device","fused with the IMU in an EKF for the Wheel-Inertial baseline and as HeRO fallback","Sec. 3.1; Sec. 3.2",[],{"totalRows":115,"groupCount":116,"groups":117,"others":288},14,2,[118,259],{"slug":119,"group":120,"sourceId":5,"sourceLabel":6,"table":121,"selfRows":122,"metrics":123,"seqs":134,"entrants":145,"cells":154,"outcomes":253,"locators":254,"hardware":255,"wordings":256,"notes":257},"lion2021-table-1","lion2021:Table 1","Table 1",12,[124,128,131],{"label":125,"unit":126,"statistic":127,"alignment":45},"t(m) position RMSE","m","RMSE",{"label":129,"unit":130,"statistic":45,"alignment":45},"t(%) percentage drift in position","%",{"label":132,"unit":133,"statistic":127,"alignment":45},"R(rad) attitude RMSE","rad",[135,139,141,143],{"dataset":136,"sequence":137,"environment":138},"DARPA SubT Tunnel Circuit runs","Track A Run 1 (685 m, 1520 s)","underground experimental mine tunnels, ground robot",{"dataset":136,"sequence":140,"environment":138},"Track A Run 2 (456 m, 1190 s)",{"dataset":136,"sequence":142,"environment":138},"Track B Run 1 (467 m, 1452 s)",{"dataset":136,"sequence":144,"environment":138},"Track B Run 2 (71 m, 246 s)",[146,148,150,151],{"name":147,"methodId":52,"linkable":80,"proposed":80,"self":80},"Wheel-Inertial",{"name":149,"methodId":52,"linkable":80,"proposed":80,"self":80},"Scan-To-Scan",{"name":7,"methodId":5,"linkable":84,"proposed":84,"self":84},{"name":152,"methodId":153,"linkable":84,"proposed":80,"self":80},"LOAM","loam2014",[155,159,162,164,166,168,170,172,174,176,179,181,183,185,187,189,191,193,195,197,199,201,203,205,207,209,211,213,215,217,219,221,223,224,226,228,230,232,233,235,237,239,241,243,245,247,249,251],[156,156,156,157,158,156,158,158,156],0,130.5,-1,[156,160,156,161,158,156,158,158,156],1,19.05,[156,116,156,163,158,156,158,158,156],1.6,[156,156,160,165,158,156,158,158,156],114,[156,160,160,167,158,156,158,158,156],25,[156,116,160,169,158,156,158,158,156],1.28,[156,156,116,171,158,156,158,158,156],78.21,[156,160,116,173,158,156,158,158,156],16.75,[156,116,116,175,158,156,158,158,156],0.99,[156,156,177,178,158,156,158,158,156],3,6.91,[156,160,177,180,158,156,158,158,156],9.79,[156,116,177,182,158,156,158,158,156],0.12,[160,156,156,184,158,156,158,158,156],105.47,[160,160,156,186,158,156,158,158,156],15.4,[160,116,156,188,158,156,158,158,156],0.9,[160,156,160,190,158,156,158,158,156],18.72,[160,160,160,192,158,156,158,158,156],4.11,[160,116,160,194,158,156,158,158,156],0.18,[160,156,116,196,158,156,158,158,156],56.6,[160,160,116,198,158,156,158,158,156],12.14,[160,116,116,200,158,156,158,158,156],0.79,[160,156,177,202,158,156,158,158,156],4.55,[160,160,177,204,158,156,158,158,156],6.45,[160,116,177,206,158,156,158,158,156],0.27,[116,156,156,208,158,156,158,158,156],56.92,[116,160,156,210,158,156,158,158,156],8.31,[116,116,156,212,158,156,158,158,156],0.36,[116,156,160,214,158,156,158,158,156],7,[116,160,160,216,158,156,158,158,156],1.53,[116,116,160,218,158,156,158,158,156],0.1,[116,156,116,220,158,156,158,158,156],17.59,[116,160,116,222,158,156,158,158,156],3.77,[116,116,116,206,158,156,158,158,156],[116,156,177,225,158,156,158,158,156],3.78,[116,160,177,227,158,156,158,158,156],5.36,[116,116,177,229,158,156,158,158,156],0.05,[177,156,156,231,158,156,158,158,156],10.99,[177,160,156,163,158,156,158,158,156],[177,116,156,234,158,156,158,158,156],0.14,[177,156,160,236,158,156,158,158,156],7.22,[177,160,160,238,158,156,158,158,156],1.58,[177,116,160,240,158,156,158,158,156],0.08,[177,156,116,242,158,156,158,158,156],13.21,[177,160,116,244,158,156,158,158,156],2.83,[177,116,116,246,158,156,158,158,156],0.21,[177,156,177,248,158,156,158,158,156],5.55,[177,160,177,250,158,156,158,158,156],7.87,[177,116,177,252,158,156,158,158,156],0.03,[],[121],[],[],[258],"DARPA SubT Tunnel Circuit (NIOSH experimental mines, Pittsburgh), one robot; LAMP output used as ground truth; LiDAR odometry 10 Hz; LION sliding window 3 s",{"slug":260,"group":261,"sourceId":5,"sourceLabel":6,"table":262,"selfRows":116,"metrics":263,"seqs":267,"entrants":272,"cells":277,"outcomes":281,"locators":282,"hardware":284,"wordings":285,"notes":286},"lion2021-text-sec-3-2","lion2021:Text Sec.3.2","Text Sec.3.2",[264],{"label":265,"unit":126,"statistic":45,"alignment":266},"total error when the robot goes back to the original position (approximately)","none",[268],{"dataset":269,"sequence":270,"environment":271},"JPL office-like environment","corridor loop","office corridor lacking LiDAR features",[273,275],{"name":274,"methodId":5,"linkable":84,"proposed":80,"self":84},"LION without observability module",{"name":276,"methodId":5,"linkable":84,"proposed":84,"self":84},"LION with observability module (HeRO switches to WIO in the corridor)",[278,280],[156,156,156,279,158,156,158,158,156],9,[160,156,156,160,158,156,158,158,156],[],[283],"Sec. 3.2; Fig. 10",[],[],[287],"Office-like environment with a featureless corridor section; total translation error when the robot returns to the start, before loop closure; values given as approximately",[],1790510661617]