15.3.1.13.1 Localization, LiDAR, Laser, Depth, 3D Data, Range Based

Chapter Contents (Back)
Localization. LiDAR. Depth.

Chang, H.D., Kim, K.I., Poston, T.,
An Accurate 3D Localization of a Camera Using a Guide-Mark,
PRL(16), No. 7, July 1995, pp. 749-757. BibRef 9507

Patruno, C., Marani, R., Nitti, M., d'Orazio, T., Stella, E.,
An Embedded Vision System for Real-Time Autonomous Localization Using Laser Profilometry,
ITS(16), No. 6, December 2015, pp. 3482-3495.
IEEE DOI 1512
Embedded systems BibRef

Lehtola, V.V.[Ville V.], Virtanen, J.P.[Juho-Pekka], Vaaja, M.T.[Matti T.], Hyyppä, H.[Hannu], Nüchter, A.[Andreas],
Localization of a mobile laser scanner via dimensional reduction,
PandRS(121), No. 1, 2016, pp. 48-59.
Elsevier DOI 1609
Localization BibRef

Porzi, L.[Lorenzo], Bulò, S.R.[Samuel Rota], Lanz, O.[Oswald], Valigi, P.[Paolo], Ricci, E.[Elisa],
An automatic image-to-DEM alignment approach for annotating mountains pictures on a smartphone,
MVA(28), No. 1-2, February 2017, pp. 101-115.
Springer DOI 1702
BibRef

Jiang, L.[Ling], Ling, D.Q.[De-Quan], Zhao, M.W.[Ming-Wei], Wang, C.[Chun], Liang, Q.H.[Qiu-Hua], Liu, K.[Kai],
Effective Identification of Terrain Positions from Gridded DEM Data Using Multimodal Classification Integration,
IJGI(7), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Zheng, L.[Li], Li, Y.H.[Yu-Hao], Sun, M.[Meng], Ji, Z.[Zheng], Yu, M.Z.[Man-Zhu], Shu, Q.B.[Qing-Bo],
Non-Rigid Vehicle-Borne LiDAR-Assisted Aerotriangulation,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Yin, H.[Huan], Wang, Y.[Yue], Ding, X.Q.[Xia-Qing], Tang, L.[Li], Huang, S.D.[Shou-Dong], Xiong, R.[Rong],
3D LiDAR-Based Global Localization Using Siamese Neural Network,
ITS(21), No. 4, April 2020, pp. 1380-1392.
IEEE DOI 2004
Laser radar, Pose estimation, Neural networks, Task analysis, Robot sensing systems, Measurement, global localization BibRef

Wang, T.[Teng], Somani, A.K.[Arun K.],
Aerial-DEM geolocalization for GPS-denied UAS navigation,
MVA(31), No. 1, January 2020, pp. Article 3.
Springer DOI 2001
BibRef

Mayalu, A.[Alfred], Kochersberger, K.[Kevin], Jenkins, B.[Barry], Malassenet, F.[François],
Lidar Data Reduction for Unmanned Systems Navigation in Urban Canyon,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Yu, S.S.[Shang-Shu], Wang, C.[Cheng], Yu, Z.L.[Zeng-Lei], Li, X.[Xin], Cheng, M.[Ming], Zang, Y.[Yu],
Deep regression for LiDAR-based localization in dense urban areas,
PandRS(172), 2021, pp. 240-252.
Elsevier DOI 2101
LiDAR-based localization, Deep regression, Multi-task learning, Residual connection, Inter-task constraint loss BibRef

Zang, Y.[Yufu], Meng, F.C.[Fan-Cong], Lindenbergh, R.[Roderik], Truong-Hong, L.[Linh], Li, B.[Bijun],
Deep Localization of Static Scans in Mobile Mapping Point Clouds,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Lin, X.[Xiaohu], Wang, F.[Fuhong], Yang, B.[Bisheng], Zhang, W.[Wanwei],
Autonomous Vehicle Localization with Prior Visual Point Cloud Map Constraints in GNSS-Challenged Environments,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

de Paula Veronese, L., Auat-Cheein, F., Mutz, F., Oliveira-Santos, T., Guivant, J.E., de Aguiar, E., Badue, C., de Souza, A.F.,
Evaluating the Limits of a LiDAR for an Autonomous Driving Localization,
ITS(22), No. 3, March 2021, pp. 1449-1458.
IEEE DOI 2103
Roads, Laser radar, Satellites, Sensor phenomena and characterization, Automobiles, particle filter BibRef

Li, W.Y.[Wen-Yi], Liu, G.[Gang], Cui, X.W.[Xiao-Wei], Lu, M.Q.[Ming-Quan],
Feature-Aided RTK/LiDAR/INS Integrated Positioning System with Parallel Filters in the Ambiguity-Position-Joint Domain for Urban Environments,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Wang, Y.S.[Yu-Sheng], Lou, Y.D.[Yi-Dong], Zhang, Y.[Yi], Song, W.W.[Wei-Wei], Huang, F.[Fei], Tu, Z.Y.[Zhi-Yong],
A Robust Framework for Simultaneous Localization and Mapping with Multiple Non-Repetitive Scanning Lidars,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Sugiura, K.[Keisuke], Matsutani, H.[Hiroki],
An FPGA Acceleration and Optimization Techniques for 2D LiDAR SLAM Algorithm,
IEICE(E104-D), No. 6, June 2021, pp. 789-800.
WWW Link. 2106
BibRef

Gong, Y.[Yansong], Sun, F.C.[Feng-Chi], Yuan, J.[Jing], Zhu, W.B.[Wen-Bin], Sun, Q.[Qinxuan],
A two-level framework for place recognition with 3D LiDAR based on spatial relation graph,
PR(120), 2021, pp. 108171.
Elsevier DOI 2109
Place recognition, 3D LiDAR, Spatial relation graph, Two-level framework BibRef

Zhang, J.J.[Jun-Jie], Khoshelham, K.[Kourosh], Khodabandeh, A.[Amir],
Seamless Vehicle Positioning by Lidar-GNSS Integration: Standalone and Multi-Epoch Scenarios,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Javanmardi, E.[Ehsan], Javanmardi, M.[Mahdi], Gu, Y.[Yanlei], Kamijo, S.[Shunsuke],
Pre-Estimating Self-Localization Error of NDT-Based Map-Matching From Map Only,
ITS(22), No. 12, December 2021, pp. 7652-7666.
IEEE DOI 2112
Autonomous vehicles, Sensors, Laser radar, Layout, Uncertainty, Gaussian distribution, LiDAR BibRef

Xu, D.[Dong], Liu, J.B.[Jing-Bin], Hyyppä, J.[Juha], Liang, Y.[Yifan], Tao, W.[Wuyong],
A heterogeneous 3D map-based place recognition solution using virtual LiDAR and a polar grid height coding image descriptor,
PandRS(183), 2022, pp. 1-18.
Elsevier DOI 2201
Place recognition, Heterogeneous 3D map, Point cloud, Global feature descriptor, Polar grid height coding image BibRef

Xu, D.[Dong], Liu, J.B.[Jing-Bin], Liang, Y.[Yifan], Lv, X.F.[Xuan-Fan], Hyyppä, J.[Juha],
A LiDAR-based single-shot global localization solution using a cross-section shape context descriptor,
PandRS(189), 2022, pp. 272-288.
Elsevier DOI 2206
Global localization, HD map, LiDAR, Global feature descriptor, Place recognition BibRef

Salles, R.N.[Roberto Neves], de Campos Velho, H.F.[Haroldo Fraga], Shiguemori, E.H.[Elcio Hideiti],
Automatic Position Estimation Based on Lidar X Lidar Data for Autonomous Aerial Navigation in the Amazon Forest Region,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Hui, L.[Le], Cheng, M.M.[Ming-Mei], Xie, J.[Jin], Yang, J.[Jian], Cheng, M.M.[Ming-Ming],
Efficient 3D Point Cloud Feature Learning for Large-Scale Place Recognition,
IP(31), 2022, pp. 1258-1270.
IEEE DOI 2202
Power transformer insulation, Electric vehicle charging, Transformers, Training, Windings, Optimization, global descriptor BibRef

Hui, L.[Le], Yang, H.[Hang], Cheng, M.M.[Ming-Mei], Xie, J.[Jin], Yang, J.[Jian],
Pyramid Point Cloud Transformer for Large-Scale Place Recognition,
ICCV21(6078-6087)
IEEE DOI 2203
Point cloud compression, Deep learning, Codes, Aggregates, Feature extraction, Transformers, Stereo, Recognition and classification BibRef

Shi, C.H.[Chen-Hui], Li, J.[Jing], Gong, J.H.[Jian-Hua], Yang, B.H.[Bang-Hui], Zhang, G.Y.[Guo-Yong],
An improved lightweight deep neural network with knowledge distillation for local feature extraction and visual localization using images and LiDAR point clouds,
PandRS(184), 2022, pp. 177-188.
Elsevier DOI 2202
Deep local features, Lightweight network, Knowledge distillation, Visual localization, LiDAR, Extreme lighting conditions BibRef

Yan, L.[Li], Hu, X.[Xiao], Zhao, L.[Leyang], Chen, Y.[Yu], Wei, P.C.[Peng-Cheng], Xie, H.[Hong],
DGS-SLAM: A Fast and Robust RGBD SLAM in Dynamic Environments Combined by Geometric and Semantic Information,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Chen, Z.J.[Zhi-Jian], Xu, A.G.[Ai-Gong], Sui, X.[Xin], Wang, C.Q.[Chang-Qiang], Wang, S.[Siyu], Gao, J.X.[Jia-Xin], Shi, Z.X.[Zheng-Xu],
Improved-UWB/LiDAR-SLAM Tightly Coupled Positioning System with NLOS Identification Using a LiDAR Point Cloud in GNSS-Denied Environments,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Niewola, A.[Adam],
Mobile Robot 6-D Localization Using 3-D Gaussian Mixture Maps in GPS-Denied Environments,
IEEE_Int_Sys(37), No. 1, January 2022, pp. 79-88.
IEEE DOI 2205
Mobile robots, Robots, Laser radar, Sensors, Feature extraction, Robot kinematics BibRef

Lee, S.[Soomok], Seo, S.W.[Seung-Woo],
Fail-Safe Multi-Modal Localization Framework Using Heterogeneous Map-Matching Sources,
ITS(23), No. 5, May 2022, pp. 4008-4020.
IEEE DOI 2205
Sensors, Laser radar, Sensor systems, Roads, Cameras, Sensor phenomena and characterization, autonomous vehicle BibRef

Yu, S.S.[Shang-Shu], Wang, C.[Cheng], Wen, C.L.[Cheng-Lu], Cheng, M.[Ming], Liu, M.H.[Ming-Hao], Zhang, Z.H.[Zhi-Hong], Li, X.[Xin],
LiDAR-based localization using universal encoding and memory-aware regression,
PR(128), 2022, pp. 108685.
Elsevier DOI 2205
BibRef
And: Corrigendum: PR(132), 2022, pp. 108915.
Elsevier DOI 2209
LiDAR localization, Absolute pose regression, Universal encoding, Privacy preserving, Memory-aware regression BibRef

Dai, D.[Deyun], Wang, J.[Jikai], Chen, Z.H.[Zong-Hai], Bao, P.[Peng],
SC-LPR: Spatiotemporal context based LiDAR place recognition,
PRL(156), 2022, pp. 160-166.
Elsevier DOI 2205
Place recognition, 3D Lidar scans, Spatiotemporal information, Cosine tensor network BibRef

Zhao, P.[Pufan], Li, S.[Song], Ma, Y.[Yue], Liu, X.Y.[Xin-Yuan], Yang, J.[Jian], Yu, D.[Dian],
A new terrain matching method for estimating laser pointing and ranging systematic biases for spaceborne photon-counting laser altimeters,
PandRS(188), 2022, pp. 220-236.
Elsevier DOI 2205
Laser altimeter, Photon-counting, Systematic bias, Geolocation accuracy, Terrain matching, ICESat-2 BibRef

Gao, F.Z.[Fang-Zheng], Tang, W.J.[Wen-Jun], Huang, J.[Jiacai], Chen, H.Y.[Hai-Yang],
Positioning of Quadruped Robot Based on Tightly Coupled LiDAR Vision Inertial Odometer,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Yin, H.[Huan], Chen, R.J.[Run-Jian], Wang, Y.[Yue], Xiong, R.[Rong],
RaLL: End-to-End Radar Localization on Lidar Map Using Differentiable Measurement Model,
ITS(23), No. 7, July 2022, pp. 6737-6750.
IEEE DOI 2207
Radar, Laser radar, Location awareness, Radar tracking, Simultaneous localization and mapping, Neural networks, Kalman filter BibRef

Liu, H.[Hong], Pan, S.[Shuguo], Gao, W.[Wang], Ma, C.[Chun], Jia, F.S.[Feng-Shuo], Lu, X.Y.[Xin-Yu],
LIDAR-Inertial Real-Time State Estimator with Rod-Shaped and Planar Feature,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Chou, C.C.[Chih-Chung], Chou, C.F.[Cheng-Fu],
Efficient and Accurate Tightly-Coupled Visual-Lidar SLAM,
ITS(23), No. 9, September 2022, pp. 14509-14523.
IEEE DOI 2209
Laser radar, Simultaneous localization and mapping, Visualization, Cameras, Point cloud compression, Bundle adjustment, vision BibRef

Xie, Y.T.[Yu-Ting], Zhang, Y.[Yachen], Chen, L.[Long], Cheng, H.[Hui], Tu, W.[Wei], Cao, D.[Dongpu], Li, Q.Q.[Qing-Quan],
RDC-SLAM: A Real-Time Distributed Cooperative SLAM System Based on 3D LiDAR,
ITS(23), No. 9, September 2022, pp. 14721-14730.
IEEE DOI 2209
Simultaneous localization and mapping, Robots, Robot kinematics, Laser radar, Task analysis, Real-time systems, 3D LiDAR, distributed system BibRef

Chen, Z.J.[Zhi-Jian], Xu, A.[Aigong], Sui, X.[Xin], Hao, Y.T.[Yu-Ting], Zhang, C.[Cong], Shi, Z.X.[Zheng-Xu],
NLOS Identification- and Correction-Focused Fusion of UWB and LiDAR-SLAM Based on Factor Graph Optimization for High-Precision Positioning with Reduced Drift,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef


Kim, J.[Junho], Choi, C.[Changwoon], Jang, H.[Hojun], Kim, Y.M.[Young Min],
PICCOLO: Point Cloud-Centric Omnidirectional Localization,
ICCV21(3293-3303)
IEEE DOI 2203
Location awareness, Point cloud compression, Training, Cloud computing, Visualization, Image color analysis, Vision for robotics and autonomous vehicles BibRef

Xia, Y.[Yan], Xu, Y.S.[Yu-Sheng], Li, S.[Shuang], Wang, R.[Rui], Du, J.[Juan], Cremers, D.[Daniel], Stilla, U.[Uwe],
SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition,
CVPR21(11343-11352)
IEEE DOI 2111
Measurement, Codes, Benchmark testing, Encoding, Pattern recognition BibRef

Komorowski, J.[Jacek],
MinkLoc3D: Point Cloud Based Large-Scale Place Recognition,
WACV21(1789-1798)
IEEE DOI 2106
Convolutional codes, Training, Location awareness, Learning systems, Computer architecture BibRef

Sunegård, A., Svensson, L., Sattler, T.,
Deep LiDAR localization using optical flow sensor-map correspondences,
3DV20(838-847)
IEEE DOI 2102
Location awareness, Laser radar, Correlation, Transforms, Optical sensors BibRef

Lee, J., Bae, J., Choi, Y., Park, I., Hong, S., Sohn, H.,
Point Cloud Transformation Using Sensor Calibration Information for Map Data Adjustment,
ISPRS20(B3:521-525).
DOI Link 2012
Autonomous vehicle localization, GNSS is not enough. Use Lidar and model. BibRef

Shi, T., Shen, S., Gao, X., Zhu, L.,
Visual Localization Using Sparse Semantic 3D Map,
ICIP19(315-319)
IEEE DOI 1910
Visual localization, semantic segmentation, image retrieval, camera pose estimation BibRef

Wang, P.[Peng], Yang, R.G.[Rui-Gang], Cao, B.B.[Bin-Bin], Xu, W.[Wei], Lin, Y.Q.[Yuan-Qing],
DeLS-3D: Deep Localization and Segmentation with a 3D Semantic Map,
CVPR18(5860-5869)
IEEE DOI 1812
For driving or augmented reality. Cameras, Semantics, Image segmentation, Pose estimation, Streaming media, Sensors BibRef

Sun, X., Xie, Y., Luo, P., Wang, L.,
A Dataset for Benchmarking Image-Based Localization,
CVPR17(5641-5649)
IEEE DOI 1711
Cameras, Laser radar, Measurement, Solid modeling, Training, Visualization BibRef

Xavier, R.S., da Silva, B.M.F., Gonzalves, L.M.G.,
Accuracy Analysis of Augmented Reality Markers for Visual Mapping and Localization,
WVC17(73-77)
IEEE DOI 1804
SLAM (robots), augmented reality, cameras, image reconstruction, pose estimation, robot vision, 3D scene reconstruction, Visualization BibRef

Gordon, M.[Marvin], Hebel, M.[Marcus], Arens, M.[Michael],
A Descriptor and Voting Scheme for Fast 3D Self-Localization in Man-Made Environments,
CRV16(319-326)
IEEE DOI 1612
3D descriptors; Hough voting; LIDAR; MLS; geometric validation BibRef

Sizikova, E.[Elena], Singh, V.K.[Vivek K.], Georgescu, B.[Bogdan], Halber, M.[Maciej], Ma, K.[Kai], Chen, T.[Terrence],
Enhancing Place Recognition Using Joint Intensity: Depth Analysis and Synthetic Data,
VARVAI16(III: 901-908).
Springer DOI 1611
BibRef

Beach, G.[Glenn], Cohen, C.J.[Charles J.], Haanpaa, D.[Doug], Rowe, S.[Steve], Mahal, P.[Pritpaul],
3D camera identification for enabling robotic manipulation,
AIPR15(1-6)
IEEE DOI 1605
cameras BibRef

Milford, M.[Michael], Lowry, S.[Stephanie], Sunderhauf, N.[Niko], Shirazi, S.[Sareh], Pepperell, E.[Edward], Upcroft, B.[Ben], Shen, C.H.[Chun-Hua], Lin, G.[Guosheng], Liu, F.[Fayao], Cadena, C.[Cesar], Reid, I.D.[Ian D.],
Sequence searching with deep-learnt depth for condition- and viewpoint-invariant route-based place recognition,
CVVT15(18-25)
IEEE DOI 1510
Computational modeling BibRef

Kanai, S., Hatakeyama, R., Date, H.,
Improvement of 3D Monte Carlo Localization Using a Depth Camera and Terrestrial Laser Scanner,
Seamless15(61-66).
DOI Link 1508
BibRef

Ventura, J.[Jonathan], Arth, C.[Clemens], Reitmayr, G.[Gerhard], Schmalstieg, D.[Dieter],
A Minimal Solution to the Generalized Pose-and-Scale Problem,
CVPR14(422-429)
IEEE DOI 1409
3d computer vision BibRef

Hao, Q.A.[Qi-Ang], Cai, R.[Rui], Li, Z.W.[Zhi-Wei], Zhang, L.[Lei], Pang, Y.W.[Yan-Wei], Wu, F.[Feng],
3D visual phrases for landmark recognition,
CVPR12(3594-3601).
IEEE DOI 1208
Triangular facet on the surface. BibRef

Shen, J.L.[Jia-Li], Miller, P., Zhou, H.Y.[Hui-Yu], Loughlin, M.,
Multi-camera detection association for 3D localisation,
MultiCamera11(480-485).
IEEE DOI 1111
BibRef

Li, Y.P.[Yun-Peng], Snavely, N.[Noah], Huttenlocher, D.P.[Dan P.], Fua, P.[Pascal],
Worldwide Pose Estimation Using 3D Point Clouds,
ECCV12(I: 15-29).
Springer DOI 1210
BibRef

Zhu, Z.W.[Zhi-Wei], Chiu, H.P.[Han-Pang], Oskiper, T.[Taragay], Ali, S.[Saad], Hadsell, R.[Raia], Samarasekera, S.[Supun], Kumar, R.[Rakesh],
High-precision localization using visual landmarks fused with range data,
CVPR11(81-88).
IEEE DOI 1106
BibRef

Tong, C.H.[Chi Hay], Barfoot, T.D.[Timothy D.],
A Comparison of the EKF, SPKF, and the Bayes Filter for Landmark-Based Localization,
CRV10(199-206).
IEEE DOI 1005
BibRef

Li, Y.P.[Yun-Peng], Snavely, N.[Noah], Huttenlocher, D.P.[Daniel P.],
Location Recognition Using Prioritized Feature Matching,
ECCV10(II: 791-804).
Springer DOI 1009
BibRef

Yousif, H.[Hamad], Li, J.[Jonathan], Chapman, M.[Mike],
Enhancement of positioning accuracy of terrestrial LiDAR mobile mapping systems,
CGC10(48).
PDF File. 1006
BibRef

Yousif, H.[Hamad], Li, J.[Jonathan], Shu, Y., Chapman, M.[Mike],
Accuracy Enhancement Of Terrestrial Mobile Lidar Data Using Theory Of Assimilation,
CloseRange10(xx-yy).
PDF File. 1006
BibRef

Brenner, C.[Claus],
Vehicle Localization using Landmarks obtained by a Lidar Mobile Mapping System,
PCVIA10(A:139).
PDF File. 1009
BibRef
Earlier:
Global Localization of Vehicles Using Local Pole Patterns,
DAGM09(61-70).
Springer DOI 0909
First a full 3D model from scanner, extract features, then localize based on these features. BibRef

Brenner, C., Elias, B.,
Extracting Landmarks for Car Navigation Systems using Existing GIS Databases and Laser Scanning,
PIA05(xx-yy).
PDF File. 0509
BibRef

Moras, J., Cherfaoui, V., Bonnifait, P.,
A lidar perception scheme for intelligent vehicle navigation,
ICARCV10(1809-1814).
IEEE DOI 1109
BibRef

Zhu, Z.W.[Zhi-Wei], Oskiper, T.[Taragay], Samarasekera, S.[Supun], Kumar, R.[Rakesh], Sawhney, H.S.[Harpreet S.],
Real-time global localization with a pre-built visual landmark database,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Chin, T.J.[Tat-Jun], Goh, H.L.[Han-Lin], Lim, J.H.[Joo-Hwee],
Boosting descriptors condensed from video sequences for place recognition,
VisLoc08(1-8).
IEEE DOI 0806
BibRef

Khoury, R.,
An Enhanced Positioning Algorithm for a Self-Referencing Hand-Held 3D Sensor,
CRV06(44-44).
IEEE DOI 0607
Match triangles of features. BibRef

Bakambu, J.N., Allard, P., Dupuis, E.,
3D Terrain Modeling for Rover Localization and Navigation,
CRV06(61-61).
IEEE DOI 0607
BibRef

Lisitsyn, V.M.[Vjacheslav M.], Danovsky, V.N.[Vladislav N.], Tikhonova, S.V.[Svetlana V.],
Method of Vehicle Navigation System Correction Based on Processing of Distance Images Obtained by Laser Locator,
PCV02(B: 157). 0305
BibRef

Wolf, J.[Jürgen], Burgard, W.[Wolfram], Burkhardt, H.[Hans],
Using an Image Retrieval System for Vision-Based Mobile Robot Localization,
CIVR02(108-119).
Springer DOI 0208
BibRef

Dellaert, F.[Frank], Burgard, W.[Wolfram], Fox, D.[Dieter], Thrun, S.[Sebastian],
Using the Condensation Algorithm for Robust, Vision-based Mobile Robot Localization,
CVPR99(II: 588-594).
IEEE DOI Locate where you are and generate map. BibRef 9900

Haehnel, D.[Dirk], Burgard, W.[Wolfram], Fox, D.[Dieter], Thrun, S.[Sebastian],
An efficient FastSLAM algorithm for generating maps of large-scale cyclic environments from raw laser range measurements,
IROS03(xx-yy). BibRef 0300

Burgard, W.[Wolfram], Fox, D.[Dieter], Thrun, S.[Sebastian],
Active Mobile Robot Localization,
IJCAI97(1346-1352). BibRef 9700

Thrun, S.[Sebastian], Burgard, W.[Wolfram], Fox, D.[Dieter],
A Probabilistic Approach for Concurrent Map Acquisition and Localization for Mobile Robots,
CMU-CS-TR--97-183, October 1997.
HTML Version. BibRef 9710

Thrun, S.[Sebastian],
A Bayesian Approach to Landmark Discovery and Active Perception in Mobile Robot Navigation,
CMU-CS-TR-96-122, May 1996.
PS File. BibRef 9605

Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Localization, Georeference, Urban Regions, City Models, Building Models .


Last update:Sep 28, 2022 at 16:10:08