LEADER 03249nam 2200481 450 001 9910686482003321 005 20230731000211.0 010 $a3-031-24017-0 024 7 $a10.1007/978-3-031-24017-1 035 $a(CKB)5840000000241873 035 $a(DE-He213)978-3-031-24017-1 035 $a(MiAaPQ)EBC7236738 035 $a(Au-PeEL)EBL7236738 035 $a(PPN)269655441 035 $a(EXLCZ)995840000000241873 100 $a20230731d2023 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSwitchable constraints for robust simultaneous localization and mapping and satellite-based localization /$fNiko Su?nderhauf 205 $a1st ed. 2023. 210 1$aCham, Switzerland :$cSpringer,$d[2023] 210 4$dİ2023 215 $a1 online resource (XIV, 184 p. 81 illus., 76 illus. in color.) 225 1 $aSpringer Tracts in Advanced Robotics,$x1610-742X ;$v137 311 $a3-031-24015-4 320 $aIncludes bibliographical references. 327 $aSimultaneous Localization And Mapping -- Least Squares Optimization -- Motivation - When Optimization Fails -- A Robust Back-End for SLAM -- Evaluation. 330 $aSimultaneous Localization and Mapping (SLAM) has been a long-standing research problem in robotics. It describes the problem of a robot mapping an unknown environment, while simultaneously localizing in it with the help of the incomplete map. This book describes a technique called Switchable Constraints. Switchable Constraints help to increase the robustness of SLAM against data association errors and in particular against false positive loop closure detections. Such false positive loop closure detections can occur when the robot erroneously assumes it re-observed a landmark it has already mapped or when the appearance of the observed surroundings is very similar to the appearance of other places in the map. Ambiguous observations and appearances are very common in human-made environments such as office floors or suburban streets, making robustness against spurious observations a key challenge in SLAM. The book summarizes the foundations of factor graph-based SLAM techniques. It explains the problem of data association errors before introducing the novel idea of Switchable Constraints. We present a mathematical derivation and probabilistic interpretation of Switchable Constraints along with evaluations on different datasets. The book shows that Switchable Constraints are applicable beyond SLAM problems and demonstrates the efficacy of this technique to improve the quality of satellite-based localization in urban environments, where multipath and non-line-of-sight situations are common error sources. 410 0$aSpringer Tracts in Advanced Robotics,$x1610-742X ;$v137 606 $aRobot vision 615 0$aRobot vision. 676 $a629.892637 700 $aSu?nderhauf$b Niko$01353548 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910686482003321 996 $aSwitchable Constraints for Robust Simultaneous Localization and Mapping and Satellite-Based Localization$93263288 997 $aUNINA