An improved LIO-SAM algorithm by integrating image information for dynamic and unstructured environments
Simultaneous localization and mapping (SLAM) is the process of estimating the trajectory of a mobile sensor carrier and creating a representation of its surroundings. Traditional SLAM algorithms are based on ‘static world assumption’ and simplify the problem by filtering out moving objects or tracki...
Saved in:
| Published in | Measurement science & technology Vol. 35; no. 9; p. 96313 |
|---|---|
| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
01.09.2024
|
| Online Access | Get full text |
| ISSN | 0957-0233 1361-6501 |
| DOI | 10.1088/1361-6501/ad56b1 |
Cover
| Abstract | Simultaneous localization and mapping (SLAM) is the process of estimating the trajectory of a mobile sensor carrier and creating a representation of its surroundings. Traditional SLAM algorithms are based on ‘static world assumption’ and simplify the problem by filtering out moving objects or tracking them separately in complex dynamic environments. However, this strong assumption restricts the application of SLAM algorithms on highly dynamic and unstructured environments. In order to resolve above problem, this paper propose an improved object-aware dynamic SLAM system by integrating image information, i.e. semantic and velocity information. Firstly, we adopt deep learning method to detect both the 2D and 3D bounding boxes of objects in the environment. This information is then used to perform multi-view, multi-dimensional bundle optimization to jointly refine the poses of camera, object, and point. Secondly, 2D detection results from image and 3D detection results from lidar are integrated by the joint probabilistic data association data association algorithm to facilitate object-level data association. We also calculate 2D and 3D motion velocity and this information is used to constraint the motion of the object. Finally, we perform comprehensive experiments on different datasets, including NCLT, M2DGR, and KITTI to prove the performance of the proposed method. |
|---|---|
| AbstractList | Simultaneous localization and mapping (SLAM) is the process of estimating the trajectory of a mobile sensor carrier and creating a representation of its surroundings. Traditional SLAM algorithms are based on ‘static world assumption’ and simplify the problem by filtering out moving objects or tracking them separately in complex dynamic environments. However, this strong assumption restricts the application of SLAM algorithms on highly dynamic and unstructured environments. In order to resolve above problem, this paper propose an improved object-aware dynamic SLAM system by integrating image information, i.e. semantic and velocity information. Firstly, we adopt deep learning method to detect both the 2D and 3D bounding boxes of objects in the environment. This information is then used to perform multi-view, multi-dimensional bundle optimization to jointly refine the poses of camera, object, and point. Secondly, 2D detection results from image and 3D detection results from lidar are integrated by the joint probabilistic data association data association algorithm to facilitate object-level data association. We also calculate 2D and 3D motion velocity and this information is used to constraint the motion of the object. Finally, we perform comprehensive experiments on different datasets, including NCLT, M2DGR, and KITTI to prove the performance of the proposed method. |
| Author | Fan, Hao Chen, Xi Fang, Yongfeng Wu, Yuhan Chen, Shaofeng Sun, Bingyu Luo, Jiyu Meng, Xinyu |
| Author_xml | – sequence: 1 givenname: Xinyu orcidid: 0009-0007-8392-7408 surname: Meng fullname: Meng, Xinyu – sequence: 2 givenname: Xi surname: Chen fullname: Chen, Xi – sequence: 3 givenname: Shaofeng surname: Chen fullname: Chen, Shaofeng – sequence: 4 givenname: Yongfeng surname: Fang fullname: Fang, Yongfeng – sequence: 5 givenname: Hao surname: Fan fullname: Fan, Hao – sequence: 6 givenname: Jiyu surname: Luo fullname: Luo, Jiyu – sequence: 7 givenname: Yuhan surname: Wu fullname: Wu, Yuhan – sequence: 8 givenname: Bingyu surname: Sun fullname: Sun, Bingyu |
| BookMark | eNo9kMtqwzAQRUVJoU7afZf6ATcaK5KtpQl9BFyyaLs2siQ7LrEUJCWQv69CQlczcxgulzNHM-usQegZyAuQqloC5ZBzRmApNeMd3KHsH81QRgQrc1JQ-oDmIfwSQkoiRIZ2tcXjdPDuZDRuNtv8q_7Ecj84P8bdhLszHm00g5dxtEP6lINJpHd-SsRZnDasz1ZOo8LSany0Ifqjikef8ow9jd7ZydgYHtF9L_fBPN3mAv28vX6vP_Jm-75Z102uQPCY6paUFZUojOCaASipSbfifVGtKGfpTJxxYCVIrgsq-gpUoToqpeG9ZEAXiFxzlXcheNO3B59q-3MLpL2Yai9a2ouW9mqK_gEc-V-F |
| Cites_doi | 10.1109/LRA.2021.3138527 10.1109/IROS.2017.8205991 10.1109/CVPR.2019.01298 10.1109/ICRA48506.2021.9562030 10.1109/TPAMI.2007.1049 10.1109/IROS40897.2019.8968012 10.1109/TRO.2021.3133730 10.1109/IROS.2018.8594394 10.1109/ICCV.2019.00597 10.1109/LRA.2017.2653359 10.1109/ICRA48506.2021.9561996 10.1109/TRO.2023.3273180 10.1109/ICRA.2018.8461018. 10.1109/TRO.2017.2705103 10.1109/IROS.2016.7759620 10.1109/LRA.2021.3068640 10.1177/0278364915614638 10.1109/CVPR.2013.178 10.1109/TRO.2018.2853729 10.1109/IROS.2017.8206392 10.15607/RSS.2014.X.007 10.1109/LRA.2021.3056380 10.1109/IROS.2016.7759677 10.1109/TVT.2015.2388780 10.1109/CVPR.2018.00211 10.1109/IROS45743.2020.9341176 10.1109/TPAMI.2020.3023183 10.1109/ICRA.2011.5979949 10.1109/TRO.2008.2006706 10.1109/ACCESS.2019.2932301 10.1109/TVT.2020.3041852 10.1109/LRA.2022.3178150 10.1109/ICRA.2019.8793511 10.1109/ICRA40945.2020.9197567 10.1109/LRA.2021.3056072 10.1109/LRA.2022.3148465 10.1109/ICRA48506.2021.9561697 10.1109/CVPRW.2018.00070 10.1155/2008/246309 10.1109/TRO.2021.3061403 10.1109/IROS45743.2020.9340704 10.1109/ICRA.2017.7989522 10.1109/ICRA40945.2020.9196698 10.1109/IROS55552.2023.10341786 10.1007/978-3-030-01216-8_40 10.1109/TITS.2019.2892413 10.1109/TRO.2018.2875382 10.1109/TIM.2020.3024405 10.1109/IROS45743.2020.9341716 10.1109/ICRA40945.2020.9196885 10.1109/IROS40897.2019.8967746 10.1109/ISMAR.2018.00024 10.1109/3DV50981.2020.00105 10.1109/ISMAR.2011.6092378 10.1109/JOE.1983.1145560 10.1109/WACV.2015.12 10.1109/LRA.2019.2923960 10.1109/3DV53792.2021.00143 10.5555/1623264.1623280 10.1109/TRO.2015.2489498 10.1109/LRA.2022.3187506 10.1109/IROS45743.2020.9340805 10.1109/TIM.2020.3020682 10.1109/TRO.2019.2909168 10.1109/CVPR42600.2020.00224 |
| ContentType | Journal Article |
| DBID | AAYXX CITATION |
| DOI | 10.1088/1361-6501/ad56b1 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | CrossRef |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Sciences (General) Physics |
| EISSN | 1361-6501 |
| ExternalDocumentID | 10_1088_1361_6501_ad56b1 |
| GroupedDBID | -DZ -~X .DC 1JI 4.4 5B3 5GY 5PX 5VS 5ZH 7.M 7.Q AAGCD AAGID AAHTB AAJIO AAJKP AATNI AAYXX ABCXL ABHWH ABJNI ABPEJ ABQJV ABVAM ACAFW ACBEA ACGFO ACGFS ACHIP ADEQX AEFHF AEINN AENEX AFYNE AKPSB ALMA_UNASSIGNED_HOLDINGS AOAED ASPBG ATQHT AVWKF AZFZN CBCFC CEBXE CITATION CJUJL CRLBU CS3 DU5 EBS EDWGO EMSAF EPQRW EQZZN F5P IHE IJHAN IOP IZVLO KOT LAP N5L N9A P2P PJBAE R4D RIN RNS RO9 ROL RPA SY9 TAE TN5 TWZ W28 WH7 XPP YQT ZMT ~02 |
| ID | FETCH-LOGICAL-c196t-657352892e96d511cad0b46f2843651cae96561571a6d239f81c2cb3aae6fa513 |
| ISSN | 0957-0233 |
| IngestDate | Wed Oct 01 05:31:08 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 9 |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c196t-657352892e96d511cad0b46f2843651cae96561571a6d239f81c2cb3aae6fa513 |
| ORCID | 0009-0007-8392-7408 |
| ParticipantIDs | crossref_primary_10_1088_1361_6501_ad56b1 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2024-09-01 |
| PublicationDateYYYYMMDD | 2024-09-01 |
| PublicationDate_xml | – month: 09 year: 2024 text: 2024-09-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationTitle | Measurement science & technology |
| PublicationYear | 2024 |
| References | Mur-Artal (mstad56b1bib59) 2017; 33 Zuo (mstad56b1bib40) 2019 Kaess (mstad56b1bib58) 2008; 24 Ceres Solver (mstad56b1bib63) 2023 Qin (mstad56b1bib26) 2018; 34 Runz (mstad56b1bib13) 2018 Shan (mstad56b1bib35) 2020 Zhang (mstad56b1bib4) 2020 Hartley (mstad56b1bib62) 2003 Tian (mstad56b1bib71) 2020; 21 Yang (mstad56b1bib53) 2023 Davison (mstad56b1bib1) 2007; 29 Zhao (mstad56b1bib9) 2020 Li (mstad56b1bib43) 2018; vol 11206 Huang (mstad56b1bib44) 2019 Sucar (mstad56b1bib50) 2020 Huang (mstad56b1bib5) 2020 Shao (mstad56b1bib39) 2019 Wu (mstad56b1bib55) 2023; 39 Zuo (mstad56b1bib41) 2020 Salas-Moreno (mstad56b1bib48) 2013 Bescos (mstad56b1bib3) 2021; 6 Pumarola (mstad56b1bib21) 2017 Sharma (mstad56b1bib15) 2021 Gonzalez (mstad56b1bib46) 2022; 7 Karunasekera (mstad56b1bib68) 2019; 7 Yunus (mstad56b1bib8) 2021 Wang (mstad56b1bib49) 2021 Graeter (mstad56b1bib38) 2018 Lucas (mstad56b1bib61) 1981; vol 2 Ye (mstad56b1bib33) 2019 Mu (mstad56b1bib16) 2016 Hageman (mstad56b1bib29) 2021; 70 Li (mstad56b1bib25) 2022; 44 Qin (mstad56b1bib32) 2020 Wen (mstad56b1bib30) 2020; 69 Lang (mstad56b1bib67) 2019 Gonzalez (mstad56b1bib47) 2023 Zhou (mstad56b1bib7) 2019; 35 Arndt (mstad56b1bib23) 2020 Yin (mstad56b1bib65) 2022; 7 Zhang (mstad56b1bib34) 2014 Zuo (mstad56b1bib22) 2017 Yang (mstad56b1bib51) 2019; 35 Cao (mstad56b1bib10) 2022; 38 Nguyen (mstad56b1bib11) Carlevaris-Bianco (mstad56b1bib64) 2016; 35 Nicholson (mstad56b1bib52) 2018 Wang (mstad56b1bib6) 2021; 37 Sharma (mstad56b1bib70) 2018 Zhang (mstad56b1bib19) 2015; 31 Kummerle (mstad56b1bib57) 2011 Fortmann (mstad56b1bib56) 1983; 8 Zhou (mstad56b1bib24) 2015; 64 Hageman (mstad56b1bib36) 2021; 70 Liao (mstad56b1bib54) 2022; 7 Yoon (mstad56b1bib69) 2015 Mur-Artal (mstad56b1bib27) 2017; 2 Bernardin (mstad56b1bib66) 2008; 2008 Sunderhauf (mstad56b1bib17) 2017 Yang (mstad56b1bib60) 2022; 7 Liu (mstad56b1bib45) 2021; 6 Marzorati (mstad56b1bib18) 2007 Rosinol (mstad56b1bib12) 2020 Liu (mstad56b1bib28) 2018 Newcombe (mstad56b1bib2) 2011 Gomez-Ojeda (mstad56b1bib20) 2016 Wisth (mstad56b1bib37) 2021; 6 Ding (mstad56b1bib31) 2020 Shan (mstad56b1bib42) 2021 Grinvald (mstad56b1bib14) 2019; 4 |
| References_xml | – volume: 7 start-page: 2266 year: 2022 ident: mstad56b1bib65 article-title: M2DGR: a multi-sensor and multi-scenario SLAM dataset for ground robots publication-title: IEEE Robot. Autom. Lett. doi: 10.1109/LRA.2021.3138527 – year: 2017 ident: mstad56b1bib22 article-title: Robust visual SLAM with point and line features doi: 10.1109/IROS.2017.8205991 – year: 2023 ident: mstad56b1bib63 – year: 2020 ident: mstad56b1bib4 article-title: VDO-SLAM: a visual dynamic object-aware SLAM system – start-page: 12689 year: 2019 ident: mstad56b1bib67 article-title: PointPillars: fast encoders for object detection from point clouds doi: 10.1109/CVPR.2019.01298 – start-page: 6687 year: 2021 ident: mstad56b1bib8 article-title: ManhattanSLAM: robust planar tracking and mapping leveraging mixture of Manhattan frames doi: 10.1109/ICRA48506.2021.9562030 – volume: 29 start-page: 1052 year: 2007 ident: mstad56b1bib1 article-title: MonoSLAM: real-time single camera SLAM publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2007.1049 – start-page: 370 year: 2019 ident: mstad56b1bib39 article-title: Stereo visual inertial LiDAR simultaneous localization and mapping doi: 10.1109/IROS40897.2019.8968012 – volume: 38 start-page: 2004 year: 2022 ident: mstad56b1bib10 article-title: GVINS: tightly coupled GNSS–visual–inertial fusion for smooth and consistent state estimation publication-title: IEEE Trans. Robot. doi: 10.1109/TRO.2021.3133730 – start-page: 7872 year: 2018 ident: mstad56b1bib38 article-title: LIMO: lidar-monocular visual odometry doi: 10.1109/IROS.2018.8594394 – year: 2019 ident: mstad56b1bib44 article-title: ClusterSLAM: a SLAM backend for simultaneous rigid body clustering and motion estimation doi: 10.1109/ICCV.2019.00597 – volume: 2 start-page: 796 year: 2017 ident: mstad56b1bib27 article-title: Visual-inertial monocular SLAM with map reuse publication-title: IEEE Robot. Autom. Lett. doi: 10.1109/LRA.2017.2653359 – start-page: 5692 year: 2021 ident: mstad56b1bib42 article-title: LVI-SAM: tightly-coupled Lidar-visual-inertial odometry via smoothing and mapping doi: 10.1109/ICRA48506.2021.9561996 – volume: 39 start-page: 1 year: 2023 ident: mstad56b1bib55 article-title: An object SLAM framework for association, mapping, and high-level tasks publication-title: IEEE Trans. Robot. doi: 10.1109/TRO.2023.3273180 – year: 2018 ident: mstad56b1bib70 article-title: Beyond pixels: leveraging geometry and shape cues for online multi-object tracking doi: 10.1109/ICRA.2018.8461018. – volume: 33 start-page: 1255 year: 2017 ident: mstad56b1bib59 article-title: ORB-SLAM2: an open-source SLAM system for monocular, stereo, and RGB-D cameras publication-title: IEEE Trans. Robot. doi: 10.1109/TRO.2017.2705103 – start-page: 4211 year: 2016 ident: mstad56b1bib20 article-title: PL-SVO: semi-direct monocular visual odometry by combining points and line segments doi: 10.1109/IROS.2016.7759620 – volume: 6 start-page: 5191 year: 2021 ident: mstad56b1bib3 article-title: DynaSLAM II: tightly-coupled multi-object tracking and SLAM publication-title: IEEE Robot. Autom. Lett. doi: 10.1109/LRA.2021.3068640 – year: 2003 ident: mstad56b1bib62 – volume: 35 start-page: 1023 year: 2016 ident: mstad56b1bib64 article-title: University of Michigan North Campus long-term vision and lidar dataset publication-title: Int. J. Robot. Res. doi: 10.1177/0278364915614638 – start-page: 1352 year: 2013 ident: mstad56b1bib48 article-title: SLAM++: simultaneous localisation and mapping at the level of objects doi: 10.1109/CVPR.2013.178 – volume: 34 start-page: 1004 year: 2018 ident: mstad56b1bib26 article-title: VINS-mono: a robust and versatile monocular visual-inertial state estimator publication-title: IEEE Trans. Robot. doi: 10.1109/TRO.2018.2853729 – start-page: 5079 year: 2017 ident: mstad56b1bib17 article-title: Meaningful maps with object-oriented semantic mapping doi: 10.1109/IROS.2017.8206392 – year: 2014 ident: mstad56b1bib34 article-title: LOAM: lidar odometry and mapping in real-time doi: 10.15607/RSS.2014.X.007 – volume: 6 start-page: 1004 year: 2021 ident: mstad56b1bib37 article-title: Unified multi-modal landmark tracking for tightly coupled lidar-visual-inertial odometry publication-title: IEEE Robot. Autom. Lett. doi: 10.1109/LRA.2021.3056380 – start-page: 4602 year: 2016 ident: mstad56b1bib16 article-title: SLAM with objects using a nonparametric pose graph doi: 10.1109/IROS.2016.7759677 – volume: 64 start-page: 1364 year: 2015 ident: mstad56b1bib24 article-title: StructSLAM: visual SLAM with building structure lines publication-title: IEEE Trans. Veh. Technol. doi: 10.1109/TVT.2015.2388780 – start-page: 1974 year: 2018 ident: mstad56b1bib28 article-title: ICE-BA: incremental, consistent and efficient bundle adjustment for visual-inertial SLAM doi: 10.1109/CVPR.2018.00211 – start-page: 5135 year: 2020 ident: mstad56b1bib35 article-title: LIO-SAM: tightly-coupled Lidar inertial odometry via smoothing and mapping doi: 10.1109/IROS45743.2020.9341176 – volume: 44 start-page: 1503 year: 2022 ident: mstad56b1bib25 article-title: Quasi-globally optimal and near/true real-time vanishing point estimation in Manhattan world publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2020.3023183 – start-page: 3607 year: 2011 ident: mstad56b1bib57 article-title: G2o: a general framework for graph optimization doi: 10.1109/ICRA.2011.5979949 – volume: 24 start-page: 1365 year: 2008 ident: mstad56b1bib58 article-title: iSAM: incremental smoothing and mapping publication-title: IEEE Trans. Robot. doi: 10.1109/TRO.2008.2006706 – volume: 7 start-page: 104423 year: 2019 ident: mstad56b1bib68 article-title: Multiple object tracking with attention to appearance, structure, motion and size publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2932301 – volume: 69 start-page: 16057 year: 2020 ident: mstad56b1bib30 article-title: Hybrid semi-dense 3D semantic-topological mapping from stereo visual-inertial odometry SLAM with loop closure detection publication-title: IEEE Trans. Veh. Technol. doi: 10.1109/TVT.2020.3041852 – volume: 7 start-page: 6846 year: 2022 ident: mstad56b1bib46 article-title: TwistSLAM: constrained SLAM in dynamic environment publication-title: IEEE Robot. Autom. Lett. doi: 10.1109/LRA.2022.3178150 – start-page: 3144 year: 2019 ident: mstad56b1bib33 article-title: Tightly coupled 3D Lidar inertial odometry and mapping doi: 10.1109/ICRA.2019.8793511 – start-page: 8899 year: 2020 ident: mstad56b1bib32 article-title: LINS: a Lidar-inertial state estimator for robust and efficient navigation doi: 10.1109/ICRA40945.2020.9197567 – volume: 6 start-page: 1296 year: 2021 ident: mstad56b1bib45 article-title: A switching-coupled backend for simultaneous localization and dynamic object tracking publication-title: IEEE Robot. Autom. Lett. doi: 10.1109/LRA.2021.3056072 – volume: 7 start-page: 4008 year: 2022 ident: mstad56b1bib54 article-title: SO-SLAM: semantic object SLAM with scale proportional and symmetrical texture constraints publication-title: IEEE Robot. Autom. Lett. doi: 10.1109/LRA.2022.3148465 – start-page: 11626 year: 2021 ident: mstad56b1bib15 article-title: Compositional and scalable object SLAM doi: 10.1109/ICRA48506.2021.9561697 – start-page: 426 year: 2018 ident: mstad56b1bib52 article-title: QuadricSLAM: dual quadrics as SLAM landmarks doi: 10.1109/CVPRW.2018.00070 – volume: 2008 start-page: 1 year: 2008 ident: mstad56b1bib66 article-title: Evaluating multiple object tracking performance: the CLEAR MOT metrics publication-title: Eurasip J. Image Video Process. doi: 10.1155/2008/246309 – volume: 37 start-page: 1416 year: 2021 ident: mstad56b1bib6 article-title: Line flow based simultaneous localization and mapping publication-title: IEEE Trans. Robot. doi: 10.1109/TRO.2021.3061403 – start-page: 5112 year: 2020 ident: mstad56b1bib41 article-title: LIC-fusion 2.0: liDAR-inertial-camera odometry with sliding-window plane-feature tracking doi: 10.1109/IROS45743.2020.9340704 – start-page: 4503 year: 2017 ident: mstad56b1bib21 article-title: PL-SLAM: real-time monocular visual SLAM with points and lines doi: 10.1109/ICRA.2017.7989522 – year: 2023 ident: mstad56b1bib53 article-title: UniQuadric: a SLAM backend for unknown rigid object 3D tracking and light-weight modeling – start-page: 4322 year: 2020 ident: mstad56b1bib31 article-title: LiDAR inertial odometry aided robust LiDAR localization system in changing city scenes doi: 10.1109/ICRA40945.2020.9196698 – year: 2023 ident: mstad56b1bib47 article-title: TwistSLAM++: fusing multiple modalities for accurate dynamic semantic SLAM doi: 10.1109/IROS55552.2023.10341786 – volume: vol 11206 start-page: 664 year: 2018 ident: mstad56b1bib43 article-title: Stereo vision-based semantic 3D object and Ego-motion tracking for autonomous driving doi: 10.1007/978-3-030-01216-8_40 – year: 2007 ident: mstad56b1bib18 article-title: Integration of 3D lines and points in 6DoF visual SLAM by uncertain projective geometry – volume: 21 start-page: 374 year: 2020 ident: mstad56b1bib71 article-title: Online multi-object tracking using joint domain information in traffic scenarios publication-title: IEEE Trans. Intell. Transport. Syst. doi: 10.1109/TITS.2019.2892413 – volume: 35 start-page: 184 year: 2019 ident: mstad56b1bib7 article-title: Canny-VO: visual odometry With RGB-D cameras based on geometric 3-D–2-D edge alignment publication-title: IEEE Trans. Robot. doi: 10.1109/TRO.2018.2875382 – volume: 70 start-page: 1 year: 2021 ident: mstad56b1bib36 article-title: An integrated GNSS/LiDAR-SLAM pose estimation framework for large-scale map building in partially GNSS-denied environments publication-title: IEEE Trans. Instrum. Meas. doi: 10.1109/TIM.2020.3024405 – start-page: 4505 year: 2020 ident: mstad56b1bib9 article-title: TP-TIO: a robust thermal-inertial odometry with deep thermalpoint doi: 10.1109/IROS45743.2020.9341716 – ident: mstad56b1bib11 article-title: VIRAL SLAM: tightly coupled camera-IMU-UWB-Lidar SLAM – start-page: 1689 year: 2020 ident: mstad56b1bib12 article-title: Kimera: an open-source library for real-time metric-semantic localization and mapping doi: 10.1109/ICRA40945.2020.9196885 – start-page: 5848 year: 2019 ident: mstad56b1bib40 article-title: LIC-fusion: liDAR-inertial-camera odometry doi: 10.1109/IROS40897.2019.8967746 – start-page: 10 year: 2018 ident: mstad56b1bib13 article-title: MaskFusion: real-time recognition, tracking and reconstruction of multiple moving objects doi: 10.1109/ISMAR.2018.00024 – start-page: 949 year: 2020 ident: mstad56b1bib50 article-title: NodeSLAM: neural object descriptors for multi-view shape reconstruction doi: 10.1109/3DV50981.2020.00105 – start-page: 127 year: 2011 ident: mstad56b1bib2 article-title: KinectFusion: real-time dense surface mapping and tracking doi: 10.1109/ISMAR.2011.6092378 – volume: 8 start-page: 173 year: 1983 ident: mstad56b1bib56 article-title: Sonar tracking of multiple targets using joint probabilistic data association publication-title: IEEE J. Ocean. Eng. doi: 10.1109/JOE.1983.1145560 – start-page: 33 year: 2015 ident: mstad56b1bib69 article-title: Bayesian multi-object tracking using motion context from multiple objects doi: 10.1109/WACV.2015.12 – volume: 4 start-page: 3037 year: 2019 ident: mstad56b1bib14 article-title: Volumetric instance-aware semantic mapping and 3D object discovery publication-title: IEEE Robot. Autom. Lett. doi: 10.1109/LRA.2019.2923960 – start-page: 1362 year: 2021 ident: mstad56b1bib49 article-title: DSP-SLAM: object oriented SLAM with deep shape priors doi: 10.1109/3DV53792.2021.00143 – volume: vol 2 year: 1981 ident: mstad56b1bib61 article-title: An iterative image registration technique with an application to stereo vision doi: 10.5555/1623264.1623280 – volume: 31 start-page: 1364 year: 2015 ident: mstad56b1bib19 article-title: Building a 3-D line-based map using stereo SLAM publication-title: IEEE Trans. Robot. doi: 10.1109/TRO.2015.2489498 – volume: 7 start-page: 8241 year: 2022 ident: mstad56b1bib60 article-title: Lidar with velocity: correcting moving objects point cloud distortion from oscillating scanning lidars by fusion with camera publication-title: IEEE Robot. Autom. Lett. doi: 10.1109/LRA.2022.3187506 – start-page: 4917 year: 2020 ident: mstad56b1bib23 article-title: From points to planes—adding planar constraints to monocular SLAM factor graphs doi: 10.1109/IROS45743.2020.9340805 – volume: 70 start-page: 1 year: 2021 ident: mstad56b1bib29 article-title: Degeneration-aware outlier mitigation for visual inertial integrated navigation system in urban canyons publication-title: IEEE Trans. Instrum. Meas. doi: 10.1109/TIM.2020.3020682 – volume: 35 start-page: 925 year: 2019 ident: mstad56b1bib51 article-title: CubeSLAM: monocular 3-D Object SLAM publication-title: IEEE Trans. Robot. doi: 10.1109/TRO.2019.2909168 – start-page: 2165 year: 2020 ident: mstad56b1bib5 article-title: ClusterVO: clustering moving instances and estimating visual odometry for self and surroundings doi: 10.1109/CVPR42600.2020.00224 |
| SSID | ssj0007099 |
| Score | 2.4564207 |
| Snippet | Simultaneous localization and mapping (SLAM) is the process of estimating the trajectory of a mobile sensor carrier and creating a representation of its... |
| SourceID | crossref |
| SourceType | Index Database |
| StartPage | 96313 |
| Title | An improved LIO-SAM algorithm by integrating image information for dynamic and unstructured environments |
| Volume | 35 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVIOP databaseName: IOP Science Platform customDbUrl: eissn: 1361-6501 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0007099 issn: 0957-0233 databaseCode: IOP dateStart: 19900101 isFulltext: true titleUrlDefault: https://iopscience.iop.org/ providerName: IOP Publishing |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3fS9xAEF6uSqEvotbSVlv2oQ8V2ZpNNnvJ41FatPRqQYXrU9jdbDyhJkXvBPtX9E_uTHaTLGqh-hJyy92Q3HzMfDu_lpB3kSlFlqeCZbaKmQClMy2FZIqnRgjDE2mxd3j6TR6cii-zdDYa_QmqlpYL_cH8vrev5DFahTXQK3bJPkCzvVBYgHvQL1xBw3D9Lx1PauxyvGyugTV-PTxix5Ppnvp51sCGf36BxLIbBtE2rlxgeY4flNpXGJbuRPo2h7D002SXWJMedsCFDHY6BBX3up4ghM_iToweC2ZRg7Pz-mY5lBE4Ozc7v71yPFdNZb0jbcdDup__aOqzft3HJ2LRF2ANgcYxA2bgzJh1ZjaRnAE35KEddmNLPN7ywKiCjXD9qnfMPZhIjDx00tCvlanUfHBuXUL_ls_rKxHbHHyWFSijQBmFk_CErMbgJ_AwkMOj771vH0e5n97o3sknvkHCfv8U-05CQHQCxnKyTtb8VoNOHG42yMjWm-RpW_JrrjbJhjfrV_S9nz2--5zMJzXtIEU9pGgPKapvaAAp2kKKBpCicEc9pChAioaQoiGktsjp508nHw-YP4yDGTDSCyyRwkFAeWxzWQJLN6qMtJAV0JtEpvAR1oGLp2OuZBkneZVxExudKGVlpVKevCArdVPbl4TGMWz6lVA80phWV7pKLLYT6ajCcXLjV2S3--eKX27mSvEvPb1-wHe3ybMBoDtkBd7fvgFKudBvWy3_BSuxdVM |
| linkProvider | IOP Publishing |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=An+improved+LIO-SAM+algorithm+by+integrating+image+information+for+dynamic+and+unstructured+environments&rft.jtitle=Measurement+science+%26+technology&rft.au=Meng%2C+Xinyu&rft.au=Chen%2C+Xi&rft.au=Chen%2C+Shaofeng&rft.au=Fang%2C+Yongfeng&rft.date=2024-09-01&rft.issn=0957-0233&rft.eissn=1361-6501&rft.volume=35&rft.issue=9&rft.spage=96313&rft_id=info:doi/10.1088%2F1361-6501%2Fad56b1&rft.externalDBID=n%2Fa&rft.externalDocID=10_1088_1361_6501_ad56b1 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0957-0233&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0957-0233&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0957-0233&client=summon |