OverlapNet: a siamese network for computing LiDAR scan similarity with applications to loop closing and localization

[1]  Cyrill Stachniss,et al.  Poisson Surface Reconstruction for LiDAR Odometry and Mapping , 2021, 2021 IEEE International Conference on Robotics and Automation (ICRA).

[2]  Cyrill Stachniss,et al.  Range Image-based LiDAR Localization for Autonomous Vehicles , 2021, 2021 IEEE International Conference on Robotics and Automation (ICRA).

[3]  Cyrill Stachniss,et al.  Deep Compression for Dense Point Cloud Maps , 2021, IEEE Robotics and Automation Letters.

[4]  C. Stachniss,et al.  Learning an Overlap-based Observation Model for 3D LiDAR Localization , 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[5]  Yong Liu,et al.  Semantic Graph Based Place Recognition for 3D Point Clouds , 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[6]  Cyrill Stachniss,et al.  OverlapNet: Loop Closing for LiDAR-based SLAM , 2020, Robotics: Science and Systems.

[7]  Yue Wang,et al.  3D LiDAR-Based Global Localization Using Siamese Neural Network , 2020, IEEE Transactions on Intelligent Transportation Systems.

[8]  Tom Duckett,et al.  Localising Faster: Efficient and precise lidar-based robot localisation in large-scale environments , 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).

[9]  Cyrill Stachniss,et al.  SuMa++: Efficient LiDAR-based Semantic SLAM , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[10]  Grzegorz Cielniak,et al.  Semantically Assisted Loop Closure in SLAM Using NDT Histograms , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[11]  Cyrill Stachniss,et al.  RangeNet ++: Fast and Accurate LiDAR Semantic Segmentation , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[12]  Cyrill Stachniss,et al.  Global Localization on OpenStreetMap Using 4-bit Semantic Descriptors , 2019, 2019 European Conference on Mobile Robots (ECMR).

[13]  Wolfram Burgard,et al.  Long-Term Urban Vehicle Localization Using Pole Landmarks Extracted from 3-D Lidar Scans , 2019, 2019 European Conference on Mobile Robots (ECMR).

[14]  Raquel Urtasun,et al.  Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[15]  Raquel Urtasun,et al.  Learning to Localize Through Compressed Binary Maps , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[16]  Cyrill Stachniss,et al.  Localization with Sliding Window Factor Graphs on Third-Party Maps for Automated Driving , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[17]  Renaud Dubé,et al.  OREOS: Oriented Recognition of 3D Point Clouds in Outdoor Scenarios , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[18]  Adrian Penate-Sanchez,et al.  Learning to See the Wood for the Trees: Deep Laser Localization in Urban and Natural Environments on a CPU , 2019, IEEE Robotics and Automation Letters.

[19]  Byungjae Park,et al.  1-Day Learning, 1-Year Localization: Long-Term LiDAR Localization Using Scan Context Image , 2019, IEEE Robotics and Automation Letters.

[20]  Abel Gawel,et al.  Local Descriptor for Robust Place Recognition Using LiDAR Intensity , 2018, IEEE Robotics and Automation Letters.

[21]  Raquel Urtasun,et al.  Learning to Localize Using a LiDAR Intensity Map , 2018, CoRL.

[22]  Chen Zhang,et al.  Robust LIDAR Localization for Autonomous Driving in Rain , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[23]  Cyrill Stachniss,et al.  Efficient Surfel-Based SLAM using 3D Laser Range Data in Urban Environments , 2018, Robotics: Science and Systems.

[24]  Renaud Dubé,et al.  Delight: An Efficient Descriptor for Global Localisation Using LiDAR Intensities , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[25]  Renaud Dubé,et al.  Learning 3D Segment Descriptors for Place Recognition , 2018, ArXiv.

[26]  Gim Hee Lee,et al.  PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[27]  Cyrill Stachniss,et al.  Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics using CNNs , 2018, 2019 International Conference on Robotics and Automation (ICRA).

[28]  C. Stachniss,et al.  Improving SLAM by Exploiting Building Information from Publicly Available Maps and Localization Priors , 2017, PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science.

[29]  Li He,et al.  M2DP: A novel 3D point cloud descriptor and its application in loop closure detection , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[30]  Cyrill Stachniss,et al.  Fast range image-based segmentation of sparse 3D laser scans for online operation , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[31]  Cyrill Stachniss,et al.  Pose fusion with chain pose graphs for automated driving , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[32]  Renaud Dubé,et al.  SegMatch: Segment based place recognition in 3D point clouds , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[33]  Andy Davis,et al.  TensorFlow: A system for large-scale machine learning , 2016, OSDI.

[34]  Dirk Schulz,et al.  A fast histogram-based similarity measure for detecting loop closures in 3-D LIDAR data , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[35]  Ryan M. Eustice,et al.  Fast LIDAR localization using multiresolution Gaussian mixture maps , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[36]  Andreas Geiger,et al.  Are we ready for autonomous driving? The KITTI vision benchmark suite , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[37]  Wolfram Burgard,et al.  Place recognition in 3D scans using a combination of bag of words and point feature based relative pose estimation , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[38]  David Silver,et al.  Monte Carlo Localization and registration to prior data for outdoor navigation , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[39]  Ryan M. Eustice,et al.  Ford Campus vision and lidar data set , 2011, Int. J. Robotics Res..

[40]  Koichi Ito,et al.  A High-Accuracy Rotation Estimation Algorithm Based on 1D Phase-Only Correlation , 2007, ICIAR.

[41]  Sebastian Thrun,et al.  Map-Based Precision Vehicle Localization in Urban Environments , 2007, Robotics: Science and Systems.

[42]  Wolfram Burgard,et al.  Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters , 2007, IEEE Transactions on Robotics.

[43]  Peter J. Huber,et al.  Robust Statistics , 2005, Wiley Series in Probability and Statistics.

[44]  Wolfram Burgard,et al.  Monte Carlo Localization: Efficient Position Estimation for Mobile Robots , 1999, AAAI/IAAI.

[45]  Wolfram Burgard,et al.  Monte Carlo localization for mobile robots , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[46]  Yann LeCun,et al.  Signature Verification Using A "Siamese" Time Delay Neural Network , 1993, Int. J. Pattern Recognit. Artif. Intell..

[47]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[48]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[49]  Sebastian Thrun,et al.  Probabilistic robotics , 2002, CACM.

[50]  R. Dobrushin.  Prescribing a System of Random Variables by Conditional Distributions , 1970 .