[{"data":1,"prerenderedAt":418},["ShallowReactive",2],{"method-kaess2012isam2":3},{"method":4,"reference":61,"equipment":85,"figures":106,"results":107},{"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":28,"sensors":35,"platform":36,"estimator":38,"association":39,"timeModel":40,"deskew":41,"loopClosure":42,"globalOptimization":43,"mapRepresentation":44,"prior":45,"outputGeometry":46,"compute":47,"codeUrl":48,"codeLicense":49,"relatedVersions":50},"kaess2012isam2","Kaess et al., 2012","iSAM2","iSAM2: Incremental smoothing and mapping using the Bayes tree",2012,"classic","C03","estimation_framework_or_library","本文提出 Bayes tree 資料結構，把稀疏矩陣分解與圖模型推論連結起來，並據此發展 iSAM2。新量測加入時，iSAM2 只移除並重新消去受影響的樹頂部團（clique），再把未受影響的子樹接回；變數排序以約束式 CCOLAMD 增量進行，把最近存取的變數推向樹根。「流動式重線性化」（fluid relinearization）只在變數增量超過門檻 β 時才更新線性化點，部分狀態更新則在解的變化小於門檻 α 時停止回代。因此 iSAM2 不再需要 iSAM 的週期性批次步驟。作者在模擬與真實的 2D 位姿圖、2D 地標資料集及模擬 3D 位姿圖上，與 iSAM1、HOG-Man、SPA 比較每步計算時間與正規化 χ2。","iSAM2 uses the Bayes tree to perform fully incremental nonlinear smoothing with incremental reordering and threshold-based fluid relinearization, eliminating periodic batch steps.","full_text_reviewed","peer_reviewed_published","main_body","未在營建場域驗證。實驗為模擬資料集與真實雷射資料集（Intel、Killian Court、Victoria Park）的位姿圖或地標圖，評估每步計算時間、受影響矩陣元素數與正規化 χ2，並未涉及點雲或建物幾何精度（Comparison to other methods）。作者以大型建物多房間建圖說明部分狀態更新的直覺，但沒有對應實驗（Partial state updates）。",[20,21],"simulation","public_benchmark",[23,24,25,26,27],"Fully incremental reordering and relinearization, no periodic batch steps (abstract; Conclusion)","Lower average and overall time than SPA on every dataset where SPA was run and similar to iSAM1 overall; its maximum per-step time is still higher than SPA's except on Intel (Timing; Table 1)","Fastest average time per step on Intel (1.74 ms), Victoria Park (2.34 ms) and Torus10000 (35.2 ms) among the compared methods (Table 1)","Solution stays very close to the per-step least-squares solution in normalized chi-square, whereas iSAM1 shows larger spikes and HOG-Man consistently larger errors (Accuracy; Fig. 16)","Fill-in stays close to that of batch ordering thanks to incremental constrained ordering (Fig. 8)",[29,30,31,32,33,34],"Update steps are not constant time; large loop closings can become as expensive as a batch solution (Related work)","Timing spikes follow those of SPA but are almost an order of magnitude higher, partly because no optimized library comparable to CHOLMOD was used (Timing)","Assumes initialization close enough to the global minimum for convergence, as for any direct solver (Algorithm and complexity)","Slower than iSAM1 in average time per step on City20000, Manhattan, Killian Court, Trees10000 and Sphere2500, and slower than HOG-Man on W10000 (Table 1)","(inference from Alg. 5) Relinearization is threshold based, so linearization points of variables whose change stays below beta are not updated","(inference) Evaluation uses 2D pose graphs, 2D landmark datasets and simulated 3D pose graphs; dense LiDAR mapping workloads are not evaluated in this paper",[],[20,37],"not described in the paper (real datasets named only: Intel, Killian Court and Victoria Park laser range data)","incremental Gauss-Newton on a factor graph via the Bayes tree: cliques affected by new factors or by relinearization are removed and re-eliminated (incomplete Cholesky within cliques) and orphaned sub-trees re-attached; incremental constrained COLAMD ordering forces recently accessed variables to the root; fluid relinearization when a variable's delta exceeds beta; partial state update stops back-substitution where changes fall below alpha; exponential-map retraction for 3D rotations","not_applicable (back-end; data association supplied externally)","discrete poses","not_applicable","not_applicable (processes loop-closure factors provided by the front-end)","incremental full smoothing over all variables without periodic batch steps","pose graph and optional landmarks","none","incrementally updated trajectory and landmark estimates","online incremental; single-threaded research C++ implementation (released in gtsam) with alpha = 0.001, beta = 0.1 and relinearization every 10 steps; all timings on a laptop with an Intel 1.6 GHz i7-720 (Table 1)","https:\u002F\u002Fgithub.com\u002Fborglab\u002Fgtsam","BSD (GTSAM LICENSE.BSD)",[51,55,58],{"relation":52,"title":53,"doi_or_url":54},"conference_version","The Bayes Tree: An Algorithmic Foundation for Probabilistic Robot Mapping (WAFR 2010, Springer STAR)","10.1007\u002F978-3-642-17452-0_10",{"relation":52,"title":56,"doi_or_url":57},"iSAM2: Incremental smoothing and mapping with fluid relinearization and incremental variable reordering (ICRA 2011)","10.1109\u002Ficra.2011.5979641",{"relation":59,"title":60,"doi_or_url":48},"code_release","Source code released as part of the gtsam library (per paper); current repository borglab\u002Fgtsam",{"id":5,"kind":62,"shortName":7,"title":8,"authors":63,"year":9,"venue":70,"venueType":71,"publisher":72,"volumeIssuePages":73,"doi":74,"arxivId":75,"url":76,"firstPublicDate":77,"publicationStatus":16,"metadataStatus":78,"fulltextStatus":15,"era":10,"classicReason":79,"codeUrl":48,"cluster":11,"topics":80,"mdpi":81,"verification":82,"label":6,"fulltextRoute":83,"versionRead":84,"addedByCensus":81},"method",[64,65,66,67,68,69],"Michael Kaess","Hordur Johannsson","Richard Roberts","Viorela Ila","John J. Leonard","Frank Dellaert","The International Journal of Robotics Research","journal","SAGE","31(2):216-235","10.1177\u002F0278364911430419",null,"https:\u002F\u002Fapi.crossref.org\u002Fworks\u002F10.1177\u002F0278364911430419","2010-12","metadata_verified","principle reused: Bayes-tree incremental smoothing with fluid relinearization is the incremental optimizer inside widely used factor-graph toolkits such as GTSAM.",[11],false,"confirmed","author copy","Authors' draft 'Draft manuscript, April 6, 2011. Submitted to IJRR' (Kaess12ijrr.pdf, 19 pages), MD5-identical (316d93560a53ce00e6d9dbf6edc410fa) to the MIT DSpace deposit Leonard_iSAM2.pdf (hdl 1721.1\u002F78894), which DSpace labels 'Author's final manuscript'; the SAGE version of record was not opened",[86,92,99,102],{"category":87,"model":88,"canonical":88,"role":89,"dataset":75,"specs":90,"locator":91},"compute","Intel i7-720","compute for runtime","1.6 GHz; laptop; all timing results; iSAM2 research C++ implementation running single-threaded","Comparison to other methods",{"category":93,"model":94,"canonical":94,"role":95,"dataset":96,"specs":97,"locator":98},"lidar","laser range sensor (model not stated)","dataset sensor","Intel","laser range data converted to a 2D pose graph (910 poses, 4453 measurements)","Fig. 11; Table 1",{"category":93,"model":94,"canonical":94,"role":95,"dataset":100,"specs":101,"locator":98},"Killian Court","laser range data converted to a 2D pose graph (1941 poses, 2190 measurements)",{"category":93,"model":94,"canonical":94,"role":95,"dataset":103,"specs":104,"locator":105},"Victoria Park","laser range data with 151 landmarks, 6969 poses, 10608 measurements","Fig. 12; Table 1",[],{"totalRows":108,"groupCount":109,"groups":110,"others":417},36,1,[111],{"slug":112,"group":113,"sourceId":5,"sourceLabel":6,"table":114,"selfRows":108,"metrics":115,"seqs":130,"entrants":148,"cells":158,"outcomes":402,"locators":403,"hardware":404,"wordings":406,"notes":407},"kaess2012isam2-table-1","kaess2012isam2:Table 1","Table 1",[116,120,123,126],{"label":117,"unit":118,"statistic":119,"alignment":41},"average time per step","ms","mean",{"label":121,"unit":118,"statistic":122,"alignment":41},"standard deviation of time per step","std",{"label":124,"unit":118,"statistic":125,"alignment":41},"maximum time per step","max",{"label":127,"unit":128,"statistic":129,"alignment":41},"overall time","s","not_reported",[131,134,136,138,140,141,142,144,146],{"dataset":132,"sequence":133,"environment":20},"City20000","full sequence",{"dataset":135,"sequence":133,"environment":20},"W10000",{"dataset":137,"sequence":133,"environment":20},"Manhattan",{"dataset":96,"sequence":133,"environment":139},"real laser range data",{"dataset":100,"sequence":133,"environment":139},{"dataset":103,"sequence":133,"environment":139},{"dataset":143,"sequence":133,"environment":20},"Trees10000",{"dataset":145,"sequence":133,"environment":20},"Sphere2500",{"dataset":147,"sequence":133,"environment":20},"Torus10000",[149,151,154,156],{"name":7,"methodId":5,"linkable":150,"proposed":150,"self":150},true,{"name":152,"methodId":153,"linkable":150,"proposed":81,"self":81},"iSAM1","kaess2008isam",{"name":155,"methodId":75,"linkable":81,"proposed":81,"self":81},"HOG-Man",{"name":157,"methodId":75,"linkable":81,"proposed":81,"self":81},"SPA",[159,163,165,168,171,173,175,177,179,181,183,185,187,189,191,193,195,197,199,201,203,205,207,209,211,213,215,217,219,221,223,225,227,229,231,233,235,237,239,241,243,244,246,248,250,252,254,256,258,260,262,264,266,268,270,272,274,276,278,280,282,284,286,287,289,292,294,295,297,299,301,303,305,306,308,309,311,313,315,317,319,322,324,326,328,330,332,334,335,338,340,342,344,346,348,350,352,355,357,359,361,363,365,367,369,371,373,375,377,380,382,384,386,388,390,392,394,396,398,400],[160,160,160,161,162,160,160,162,160],0,16.1,-1,[160,109,160,164,162,160,160,162,160],65.6,[160,166,160,167,162,160,160,162,160],2,1125,[160,169,160,170,162,160,160,162,160],3,323,[109,160,160,172,162,160,160,162,160],7.05,[109,109,160,174,162,160,160,162,160],14.5,[109,166,160,176,162,160,160,162,160],308,[109,169,160,178,162,160,160,162,160],141,[166,160,160,180,162,160,160,162,160],27.4,[166,109,160,182,162,160,160,162,160],27.8,[166,166,160,184,162,160,160,162,160],146,[166,169,160,186,162,160,160,162,160],548,[169,160,160,188,162,160,160,162,160],48.7,[169,109,160,190,162,160,160,162,160],32.6,[169,166,160,192,162,160,160,162,160],140,[169,169,160,194,162,160,160,162,160],977,[160,160,109,196,162,160,160,162,109],22.4,[160,109,109,198,162,160,160,162,109],64.6,[160,166,109,200,162,160,160,162,109],901,[160,169,109,202,162,160,160,162,109],224,[109,160,109,204,162,160,160,162,109],35.7,[109,109,109,206,162,160,160,162,109],58.8,[109,166,109,208,162,160,160,162,109],683,[109,169,109,210,162,160,160,162,109],357,[166,160,109,212,162,160,160,162,109],16.4,[166,109,109,214,162,160,160,162,109],14.9,[166,166,109,216,162,160,160,162,109],147,[166,169,109,218,162,160,160,162,109],164,[169,160,109,220,162,160,160,162,109],108,[169,109,109,222,162,160,160,162,109],75.6,[169,166,109,224,162,160,160,162,109],287,[169,169,109,226,162,160,160,162,109],1081,[160,160,166,228,162,160,160,162,166],2.44,[160,109,166,230,162,160,160,162,166],7.71,[160,166,166,232,162,160,160,162,166],133,[160,169,166,234,162,160,160,162,166],8.54,[109,160,166,236,162,160,160,162,166],1.81,[109,109,166,238,162,160,160,162,166],3.69,[109,166,166,240,162,160,160,162,166],57.6,[109,169,166,242,162,160,160,162,166],6.35,[166,160,166,230,162,160,160,162,166],[166,109,166,245,162,160,160,162,166],6.91,[166,166,166,247,162,160,160,162,166],33.8,[166,169,166,249,162,160,160,162,166],27,[169,160,166,251,162,160,160,162,166],11.8,[169,109,166,253,162,160,160,162,166],8.46,[169,166,166,255,162,160,160,162,166],28.9,[169,169,166,257,162,160,160,162,166],41.1,[160,160,169,259,162,160,160,162,169],1.74,[160,109,169,261,162,160,160,162,169],1.76,[160,166,169,263,162,160,160,162,169],9.13,[160,169,169,265,162,160,160,162,169],1.59,[109,160,169,267,162,160,160,162,169],5.8,[109,109,169,269,162,160,160,162,169],8.03,[109,166,169,271,162,160,160,162,169],48.4,[109,169,169,273,162,160,160,162,169],5.28,[166,160,169,275,162,160,160,162,169],9.4,[166,109,169,277,162,160,160,162,169],12.5,[166,166,169,279,162,160,160,162,169],79.3,[166,169,169,281,162,160,160,162,169],8.55,[169,160,169,283,162,160,160,162,169],4.89,[169,109,169,285,162,160,160,162,169],3.77,[169,166,169,214,162,160,160,162,169],[169,169,169,288,162,160,160,162,169],4.44,[160,160,290,291,162,160,160,162,290],4,0.59,[160,109,290,293,162,160,160,162,290],0.8,[160,166,290,277,162,160,160,162,290],[160,169,290,296,162,160,160,162,290],1.15,[109,160,290,298,162,160,160,162,290],0.51,[109,109,290,300,162,160,160,162,290],1.13,[109,166,290,302,162,160,160,162,290],16.6,[109,169,290,304,162,160,160,162,290],0.99,[166,160,290,166,162,160,160,162,290],[166,109,290,307,162,160,160,162,290],2.41,[166,166,290,251,162,160,160,162,290],[166,169,290,310,162,160,160,162,290],3.88,[169,160,290,312,162,160,160,162,290],3.13,[169,109,290,314,162,160,160,162,290],1.89,[169,166,290,316,162,160,160,162,290],7.98,[169,169,290,318,162,160,160,162,290],6.07,[160,160,320,321,162,160,160,162,320],5,2.34,[160,109,320,323,162,160,160,162,320],7.75,[160,166,320,325,162,160,160,162,320],316,[160,169,320,327,162,160,160,162,320],16.3,[109,160,320,329,162,160,160,162,320],2.35,[109,109,320,331,162,160,160,162,320],4.82,[109,166,320,333,162,160,160,162,320],80.4,[109,169,320,212,162,160,160,162,320],[160,160,336,337,162,160,160,162,336],6,4.24,[160,109,336,339,162,160,160,162,336],6.52,[160,166,336,341,162,160,160,162,336],124,[160,169,336,343,162,160,160,162,336],42.4,[109,160,336,345,162,160,160,162,336],2.98,[109,109,336,347,162,160,160,162,336],6.7,[109,166,336,349,162,160,160,162,336],114,[109,169,336,351,162,160,160,162,336],29.8,[160,160,353,354,162,160,160,162,353],7,30.4,[160,109,353,356,162,160,160,162,353],25.5,[160,166,353,358,162,160,160,162,353],158,[160,169,353,360,162,160,160,162,353],76,[109,160,353,362,162,160,160,162,353],21.7,[109,109,353,364,162,160,160,162,353],31.3,[109,166,353,366,162,160,160,162,353],679,[109,169,353,368,162,160,160,162,353],54.3,[166,160,353,370,162,160,160,162,353],56.7,[166,109,353,372,162,160,160,162,353],40.8,[166,166,353,374,162,160,160,162,353],159,[166,169,353,376,162,160,160,162,353],142,[160,160,378,379,162,160,160,162,378],8,35.2,[160,109,378,381,162,160,160,162,378],45.7,[160,166,378,383,162,160,160,162,378],487,[160,169,378,385,162,160,160,162,378],352,[109,160,378,387,162,160,160,162,378],86.4,[109,109,378,389,162,160,160,162,378],119,[109,166,378,391,162,160,160,162,378],1824,[109,169,378,393,162,160,160,162,378],864,[166,160,378,395,162,160,160,162,378],99,[166,109,378,397,162,160,160,162,378],82.9,[166,166,378,399,162,160,160,162,378],404,[166,169,378,401,162,160,160,162,378],990,[],[114],[405],"laptop with Intel 1.6 GHz i7-720; iSAM2 single-threaded research C++ (alpha 0.001, beta 0.1, relinearization every 10 steps); iSAM1 v1.6 standard parameters; HOG-Man svn rev 14 with -update 1; SPA from ROS svn rev 36438",[],[408,409,410,411,412,413,414,415,416],"Runtime comparison (iSAM1 and HOG-Man set to solve in every step, SPA with standard parameters, iSAM2 relinearizing every 10 steps); per-step average, standard deviation and maximum in ms and overall time in s (P poses, M measurements, L landmarks); P 20000, M 26770, simulated 2D pose graph","Runtime comparison (iSAM1 and HOG-Man set to solve in every step, SPA with standard parameters, iSAM2 relinearizing every 10 steps); per-step average, standard deviation and maximum in ms and overall time in s (P poses, M measurements, L landmarks); P 10000, M 64311, simulated 2D pose graph","Runtime comparison (iSAM1 and HOG-Man set to solve in every step, SPA with standard parameters, iSAM2 relinearizing every 10 steps); per-step average, standard deviation and maximum in ms and overall time in s (P poses, M measurements, L landmarks); P 3500, M 5598, simulated 2D pose graph","Runtime comparison (iSAM1 and HOG-Man set to solve in every step, SPA with standard parameters, iSAM2 relinearizing every 10 steps); per-step average, standard deviation and maximum in ms and overall time in s (P poses, M measurements, L landmarks); P 910, M 4453, 2D pose graph from laser range data","Runtime comparison (iSAM1 and HOG-Man set to solve in every step, SPA with standard parameters, iSAM2 relinearizing every 10 steps); per-step average, standard deviation and maximum in ms and overall time in s (P poses, M measurements, L landmarks); P 1941, M 2190, 2D pose graph from laser range data","Runtime comparison (iSAM1 and HOG-Man set to solve in every step, SPA with standard parameters, iSAM2 relinearizing every 10 steps); per-step average, standard deviation and maximum in ms and overall time in s (P poses, M measurements, L landmarks); P 6969, M 10608, L 151, 2D landmarks from laser range data","Runtime comparison (iSAM1 and HOG-Man set to solve in every step, SPA with standard parameters, iSAM2 relinearizing every 10 steps); per-step average, standard deviation and maximum in ms and overall time in s (P poses, M measurements, L landmarks); P 10000, M 14442, L 100, simulated 2D landmarks","Runtime comparison (iSAM1 and HOG-Man set to solve in every step, SPA with standard parameters, iSAM2 relinearizing every 10 steps); per-step average, standard deviation and maximum in ms and overall time in s (P poses, M measurements, L landmarks); P 2500, M 4950, simulated 3D pose graph","Runtime comparison (iSAM1 and HOG-Man set to solve in every step, SPA with standard parameters, iSAM2 relinearizing every 10 steps); per-step average, standard deviation and maximum in ms and overall time in s (P poses, M measurements, L landmarks); P 10000, M 22281, simulated 3D pose graph",[],1790510654206]