├── 1VIO ├── 1 A Tutorial on Quantitative Trajectory Evaluation for Visual(-Inertial) Odometry.pdf ├── 10.Real-Time Fully Incremental Scene Understanding on Mobile Platforms.pdf ├── 11.The TUM VI Benchmark for Evaluating Visual-Inertial Odometry.pdf ├── 12.Trifo-VIO Robust and Efficient Stereo Visual Inertial Odometry using Points and Lines.pdf ├── 13.π-SoC Heterogeneous SoC Architecture for Visual Inertial SLAM Applications.pdf ├── 14.Robocentric Visual-Inertial Odometry.pdf ├── 15.Robust Visual-Inertial State Estimation with Multiple Odometries and_Efficient Mapping on an MAV with Ultra-Wide FOV Stereo Vision.pdf ├── 16.Unscented Kalman Filter on Lie Groups for Visual_Inertial Odometry.pdf ├── 2. Challenges in Monocular Visual Odometry Photometric Calibration, Motion Bias and Rolling Shutter Effect.pdf ├── 3. CVI-SLAM – Collaborative Visual-Inertial SLAM.pdf ├── 4. Embedding Temporally Consistent Depth Recovery for Real-time Dense Mapping in Visual-inertial Odometry.pdf ├── 5. Hybrid Contact Preintegration for Visual-Inertial-Contact State Estimation Using Factor Graphs.pdf ├── 6.Information Sparsification in Visual-Inertial Odometry.pdf ├── 7.Key-Frame Strategy During Fast Image-Scale Changes and Zero Motion in VIO Without Persistent Features.pdf ├── 8.On the Comparison of Gauge Freedom Handling in Optimization-based Visual-Inertial State Estimation.pdf └── 9.Online Temporal Calibration for Monocular Visual-Inertial Systems.pdf ├── 2RGBD ├── 1.Perception Based Locomotion System for a Humanoid Robot with Adaptive Footstep Compensation under Task Constraints.pdf ├── 2.Real-time 3D Reconstruction Using a Combination of Point-based and Volumetric Fusion.pdf └── 3.Edge-based Robust RGB-D Visual Odometry_Using 2-D Edge Divergence Minimization.pdf ├── 3lidar ├── 1.A Maximum Likelihood Approach to Extract Polylines from 2-D Laser Range Scans.pdf ├── 10.LeGO-LOAM_ Lightweight and Ground-Optimized_Lidar Odometry and Mapping on Variable Terrain.pdf ├── 11.LiDAR and Camera Calibration using Motions Estimated by Sensor_Fusion Odometry.pdf ├── 12.Scan Context_ Egocentric Spatial Descriptor_for Place Recognition within 3D Point Cloud Map.pdf ├── 2.A robust pose graph approach for city scale LiDAR mapping.pdf ├── 3.Dynamic Scaling Factors of Covariances for Accurate 3D Normal Distributions Transform Registration.pdf ├── 4.Integrating Deep Semantic Segmentation into 3D Point Cloud Registration.pdf ├── 5.LIMO Lidar-Monocular Visual Odometry.pdf ├── 6.LIPS LiDAR-Inertial 3D Plane SLAM.pdf ├── 7.PoseMap Lifelong, Multi-Environment 3D LiDAR Localization.pdf ├── 8.Stabilize an Unsupervised Feature Learning for LiDAR-based Place Recognition.pdf └── 9.Stereo Camera Localization in 3D LiDAR Maps.pdf ├── 4eventcamera └── 1.AsynchronousCornerDetectionandTrackingforEventCamerasinReal-Time.pdf ├── 5map ├── 1.A B-spline Mapping Framework for Long-Term Autonomous Operations.pdf ├── 2.C-blox A Scalable and Consistent TSDF-based Dense Mapping Approach.pdf ├── 3.Efficient Long-term Mapping in Dynamic Environments.pdf ├── 4.HMAPs – Hybrid Height-Voxel Maps for Environment Representation.pdf ├── 5.Human-in-the-loop Augmented Mapping.pdf └── 6.Structured Skip List A Compact Data Structure for 3D Reconstruction.pdf ├── 6slamsystem ├── 1.ArthroSLAM multi-sensor robust visual localization for minimally invasive orthopedic surgery.pdf ├── 10.Semi-Supervised SLAM Leveraging Low-Cost Sensors on Underground Autonomous Vehicles for Position Tracking.pdf ├── 11.Towards Robust Visual Odometry with a Multi-Camera System.pdf ├── 12.Fast Cylinder and Plane Extraction from Depth Cameras for Visual_Odometry.pdf ├── 13.Geometric-based Line Segment Tracking for HDR Stereo Sequences.pdf ├── 14.Multimotion Visual Odometry (MVO)__Simultaneous Estimation of Camera and Third-Party Motions.pdf ├── 15.Reliable fusion of black-box estimates of underwater localization.pdf ├── 16.Stereo Visual Odometry and Semantics based Localization of Aerial_Robots in Indoor Environments.pdf ├── 2.DynaSLAM Tracking, Mapping and Inpainting in Dynamic Scenes.pdf ├── 3.Improving Repeatability of Experiments by Automatic Evaluation of SLAM Algorithms.pdf ├── 4.Indoor Mapping and Localization for Pedestrians using Opportunistic Sensing with Smartphones.pdf ├── 5.MIS-SLAM Real-time Large Scale Dense Deformable SLAM System in Minimal Invasive Surgery Based on Heterogeneous Computing.pdf ├── 6.Omnidirectional DSO Direct Sparse Odometry with Fisheye Cameras.pdf ├── 7.OpenSeqSLAM2.0 An Open Source Toolbox for Visual Place Recognition Under Changing Conditions.pdf ├── 8.Probabilistic Dense Reconstruction from a Moving Camera.pdf └── 9.Robust Long-Term Registration of UAV Images of Crop Fields for Precision Agriculture.pdf ├── 7backend ├── 1.LDSO Direct Sparse Odometry with Loop Closure.pdf ├── 2.Predicting Objective Function Change in Pose-Graph Optimization.pdf ├── 3.Scan Similarity-based Pose Graph Construction Method for Graph SLAM.pdf ├── 4.Submap-based Pose-graph Visual SLAM A Robust Visual Exploration and Localization System.pdf └── 5.Virtual Occupancy Grid Map for Submap-based Pose Graph SLAM and Planning in 3D Environments.pdf ├── 8frontend ├── 1.A Combined RGB and Depth Descriptor for SLAM with Humanoids.pdf ├── 2.Good Feature Selection for Least Squares Pose Optimization in VOVSLAM.pdf ├── 3.HBST A Hamming Distance embedding Binary Search Tree for Feature-based Visual Place Recognition.pdf ├── 4.Keyframe-based Photometric Online Calibration and Color Correction.pdf ├── 5.Optimized Contrast Enhancements to Improve Robustness of Visual Tracking in a SLAM Relocalisation Context.pdf ├── 6.Robust Camera Pose Estimation via Consensus on Ray Bundle and Vector Field.pdf ├── 7.Unit Quaternion-based Parameterization for Point Features in Visual Navigation.pdf └── 8.Perspective Correcting Visual Odometry for Agile MAVs using a_Pixel Processor Array.pdf ├── 9deepslam ├── 1.A Variational Feature Encoding Method of 3D Object for Probabilistic Semantic SLAM.pdf ├── 10.Semantic Monocular SLAM for Highly Dynamic Environments.pdf ├── 11.Unsupervised Odometry and Depth Learning for Endoscopic Capsule_Robots.pdf ├── 2.Bayesian Information Recovery from CNN for Probabilistic Inference.pdf ├── 3.DS-SLAM A Semantic Visual SLAM towards Dynamic Environments.pdf ├── 4.Fast and Accurate Semantic Mapping through Geometric-based Incremental Segmentation.pdf ├── 5.Integrating Deep Semantic Segmentation into 3D Point Cloud Registration.pdf ├── 6.Learning monocular visual odometry with dense 3D mapping from dense 3D flow.pdf ├── 7.Localization of Classified Objects in SLAM using Nonparametric Statistics and Clustering.pdf ├── 8.Pose Estimation and Map Formation with Spiking Neural Networks towards Neuromorphic SLAM.pdf └── 9.Robust Exploration with Multiple Hypothesis Data Association.pdf ├── README.md ├── _config.yml └── 标题图.JPG /1VIO/1 A Tutorial on Quantitative Trajectory Evaluation for Visual(-Inertial) Odometry.pdf: 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Visual-Inertial State Estimation with Multiple Odometries and_Efficient Mapping on an MAV with Ultra-Wide FOV Stereo Vision.pdf -------------------------------------------------------------------------------- /1VIO/16.Unscented Kalman Filter on Lie Groups for Visual_Inertial Odometry.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/1VIO/16.Unscented Kalman Filter on Lie Groups for Visual_Inertial Odometry.pdf -------------------------------------------------------------------------------- /1VIO/2. Challenges in Monocular Visual Odometry Photometric Calibration, Motion Bias and Rolling Shutter Effect.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/1VIO/2. Challenges in Monocular Visual Odometry Photometric Calibration, Motion Bias and Rolling Shutter Effect.pdf -------------------------------------------------------------------------------- /1VIO/3. CVI-SLAM – Collaborative Visual-Inertial SLAM.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/1VIO/3. CVI-SLAM – Collaborative Visual-Inertial SLAM.pdf -------------------------------------------------------------------------------- /1VIO/4. Embedding Temporally Consistent Depth Recovery for Real-time Dense Mapping in Visual-inertial Odometry.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/1VIO/4. Embedding Temporally Consistent Depth Recovery for Real-time Dense Mapping in Visual-inertial Odometry.pdf -------------------------------------------------------------------------------- /1VIO/5. Hybrid Contact Preintegration for Visual-Inertial-Contact State Estimation Using Factor Graphs.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/1VIO/5. Hybrid Contact Preintegration for Visual-Inertial-Contact State Estimation Using Factor Graphs.pdf -------------------------------------------------------------------------------- /1VIO/6.Information Sparsification in Visual-Inertial Odometry.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/1VIO/6.Information Sparsification in Visual-Inertial Odometry.pdf -------------------------------------------------------------------------------- /1VIO/7.Key-Frame Strategy During Fast Image-Scale Changes and Zero Motion in VIO Without Persistent Features.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/1VIO/7.Key-Frame Strategy During Fast Image-Scale Changes and Zero Motion in VIO Without Persistent Features.pdf -------------------------------------------------------------------------------- /1VIO/8.On the Comparison of Gauge Freedom Handling in Optimization-based Visual-Inertial State Estimation.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/1VIO/8.On the Comparison of Gauge Freedom Handling in Optimization-based Visual-Inertial State Estimation.pdf -------------------------------------------------------------------------------- /1VIO/9.Online Temporal Calibration for Monocular Visual-Inertial Systems.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/1VIO/9.Online Temporal Calibration for Monocular Visual-Inertial Systems.pdf -------------------------------------------------------------------------------- /2RGBD/1.Perception Based Locomotion System for a Humanoid Robot with Adaptive Footstep Compensation under Task Constraints.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/2RGBD/1.Perception Based Locomotion System for a Humanoid Robot with Adaptive Footstep Compensation under Task Constraints.pdf -------------------------------------------------------------------------------- /2RGBD/2.Real-time 3D Reconstruction Using a Combination of Point-based and Volumetric Fusion.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/2RGBD/2.Real-time 3D Reconstruction Using a Combination of Point-based and Volumetric Fusion.pdf -------------------------------------------------------------------------------- /2RGBD/3.Edge-based Robust RGB-D Visual Odometry_Using 2-D Edge Divergence Minimization.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/2RGBD/3.Edge-based Robust RGB-D Visual Odometry_Using 2-D Edge Divergence Minimization.pdf -------------------------------------------------------------------------------- /3lidar/1.A Maximum Likelihood Approach to Extract Polylines from 2-D Laser Range Scans.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/3lidar/1.A Maximum Likelihood Approach to Extract Polylines from 2-D Laser Range Scans.pdf -------------------------------------------------------------------------------- /3lidar/10.LeGO-LOAM_ Lightweight and Ground-Optimized_Lidar Odometry and Mapping on Variable Terrain.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/3lidar/10.LeGO-LOAM_ Lightweight and Ground-Optimized_Lidar Odometry and Mapping on Variable Terrain.pdf -------------------------------------------------------------------------------- /3lidar/11.LiDAR and Camera Calibration using Motions Estimated by Sensor_Fusion Odometry.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/3lidar/11.LiDAR and Camera Calibration using Motions Estimated by Sensor_Fusion Odometry.pdf -------------------------------------------------------------------------------- /3lidar/12.Scan Context_ Egocentric Spatial Descriptor_for Place Recognition within 3D Point Cloud Map.pdf: 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Lidar-Monocular Visual Odometry.pdf -------------------------------------------------------------------------------- /3lidar/6.LIPS LiDAR-Inertial 3D Plane SLAM.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/3lidar/6.LIPS LiDAR-Inertial 3D Plane SLAM.pdf -------------------------------------------------------------------------------- /3lidar/7.PoseMap Lifelong, Multi-Environment 3D LiDAR Localization.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/3lidar/7.PoseMap Lifelong, Multi-Environment 3D LiDAR Localization.pdf -------------------------------------------------------------------------------- /3lidar/8.Stabilize an Unsupervised Feature Learning for LiDAR-based Place Recognition.pdf: 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Semantic Visual SLAM towards Dynamic Environments.pdf -------------------------------------------------------------------------------- /9deepslam/4.Fast and Accurate Semantic Mapping through Geometric-based Incremental Segmentation.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/9deepslam/4.Fast and Accurate Semantic Mapping through Geometric-based Incremental Segmentation.pdf -------------------------------------------------------------------------------- /9deepslam/5.Integrating Deep Semantic Segmentation into 3D Point Cloud Registration.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/9deepslam/5.Integrating Deep Semantic Segmentation into 3D Point Cloud Registration.pdf 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-------------------------------------------------------------------------------- 1 | ![](./标题图.JPG) 2 | 3 | # IROS2018 SLAM Collections 4 | ## Introduction 5 | 6 | This repository contains SLAM papers from IROS2018. Thanks for the efforts from [**PaoPaoRobot**](http://paopaorobot.org/) 7 | 8 | ## Reference 9 | **[\[泡泡前沿追踪\]跟踪SLAM前沿动态系列之IROS2018](https://mp.weixin.qq.com/s/ozj-Lq3o2Z2M9siXRbnpVw)** 10 | 11 | ## Fields 12 | ### Visual Inertial Odometry 13 | 14 | 1. **A Tutorial on Quantitative Trajectory Evaluation for Visual(-Inertial) Odometry**, Zichao Zhang, Davide Scaramuzza [\[pdf\]](http://rpg.ifi.uzh.ch/docs/IROS18_Zhang.pdf) [\[code\]](https://github.com/uzh-rpg/rpg_trajectory_evaluation) 15 | 2. **Challenges in Monocular Visual Odometry Photometric Calibration, Motion Bias and Rolling Shutter Effect**, Nan Yang 16 | , Rui Wang, Xiang Gao, and Daniel Cremers [\[pdf\]](https://arxiv.org/pdf/1705.04300.pdf) 17 | 3. **CVI-SLAM – Collaborative Visual-Inertial SLAM**, Marco Karrer, Patrik Schmuck, Margarita Chli [\[pdf\]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8360045) 18 | 4. **Embedding Temporally Consistent Depth Recovery for Real-time Dense Mapping in Visual-inertial Odometry**, Hui Cheng, Zhuoqi Zheng, Jinhao He, Chongyu Chen, Keze Wang, and Liang Lin 19 | 5. **Hybrid Contact Preintegration for Visual-Inertial-Contact State Estimation Using Factor Graphs**, Ross Hartley, Maani Ghaffari Jadidi, Lu Gan, Jiunn-Kai Huang, Jessy W. Grizzle, and Ryan M. Eustice [\[pdf\]](https://arxiv.org/pdf/1803.07531.pdf) [\[video\]](https://youtu.be/WDPhdl5g2MQ) 20 | 6. **Information Sparsification in Visual-Inertial Odometry**, Jerry Hsiung, Ming Hsiao, Eric Westman, Rafael Valencia, and Michael Kaess [\[pdf\]](https://www.ri.cmu.edu/wp-content/uploads/2018/09/Hsiung18iros.pdf) 21 | 7. **Key-Frame Strategy During Fast Image-Scale Changes and Zero Motion in VIO Without Persistent Features**, Eren Allak, Alexander Hardt-Stremayr, and Stephan Weiss 22 | 8. **On the Comparison of Gauge Freedom Handling in Optimization-based Visual-Inertial State Estimation**, Zichao Zhang, Guillermo Gallego, Davide Scaramuzza [\[pdf\]](http://rpg.ifi.uzh.ch/docs/RAL18_Zhang.pdf) 23 | 9. **Online Temporal Calibration for Monocular Visual-Inertial Systems**, Tong Qin and Shaojie Shen [\[pdf\]](https://arxiv.org/pdf/1808.00692.pdf) [\[code\]](https://github.com/HKUST-Aerial-Robotics/VINS-Mono) 24 | 10. **Real-Time Fully Incremental Scene Understanding on Mobile Platforms**, Johanna Wald, Keisuke Tateno, Jurgen Sturm, Nassir Navab, and Federico Tombari [\[pdf\]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8403286) [\[project\]](http://campar.in.tum.de/view/Chair/ProjectInSeg) 25 | 11. **The TUM VI Benchmark for Evaluating Visual-Inertial Odometry**, David Schubert, Thore Goll, Nikolaus Demmel, Vladyslav Usenko, Jorg Stuckler and Daniel Cremers [\[pdf\]](https://arxiv.org/pdf/1804.06120.pdf) [\[dataset\]](https://vision.in.tum.de/data/datasets/visual-inertial-dataset) 26 | 12. **Trifo-VIO: Robust and Efficient Stereo Visual Inertial Odometry using 27 | Points and Lines**, Feng Zheng, Grace Tsai, Zhe Zhang, Shaoshan Liu, Chen-Chi Chu, and Hongbing Hu [\[pdf\]](https://arxiv.org/pdf/1803.02403.pdf) [\[dataset\]](https://github.com/PerceptIn/IRONSIDES/wiki/Dataset) 28 | 13. **π-SoC Heterogeneous SoC Architecture for Visual Inertial SLAM Applications**, Jie Tang, Bo Yu, Shaoshan Liu, Zhe Zhang, Weikang Fang, and Yanjun Zhang 29 | 14. **Robocentric Visual-Inertial Odometry**, Zheng Huai, Guoquan Huang [\[pdf\]](https://arxiv.org/pdf/1805.04031.pdf) 30 | 15. **Robust Visual-Inertial State Estimation with Multiple Odometries and Efficient Mapping on an MAV with Ultra-Wide FOV Stereo Vision**, M. G. Müller, F. Steidle, M. J. Schuster, P. Lutz, M. Maier, S. Stoneman, T. Tomic, W. Stürzl 31 | 16. **Unscented Kalman Filter on Lie Groups for Visual_Inertial Odometry**, Martin Brossard, Silvere Bonnabel, Axel Barrau [\[pdf\]](https://hal.archives-ouvertes.fr/hal-01735542v2/document) 32 | 33 | ### RGBD Camera 34 | 35 | 1. **Perception Based Locomotion System for a Humanoid Robot with Adaptive Footstep Compensation under Task Constraints**, Iori Kumagai, Mitsuharu Morisawa, Shin’ichiro Nakaoka, Takeshi Sakaguchi, Hiroshi Kaminaga, Kenji Kaneko, Fumio Kanehiro 36 | 2. **Real-time 3D Reconstruction Using a Combination of Point-based and Volumetric Fusion** , Maik Keller, Damien Lefloch, Martin Lambers, Shahram Izadi, Tim Weyrich, Andreas Kolb [\[pdf\]](http://reality.cs.ucl.ac.uk/projects/kinect/keller13realtime.pdf) 37 | 3. **Edge-based Robust RGB-D Visual Odometry_Using 2-D Edge Divergence Minimization**, Changhyeon Kim, Pyojin Kim, Sangil Lee and H. Jin Kim 38 | 39 | ### LiDAR 40 | 41 | 1. **A Maximum Likelihood Approach to Extract Polylines from 2-D Laser Range Scans**, Alexander Schaefer, Daniel Buscher, Lukas Luft, Wolfram Burgard [\[pdf\]](http://ais.informatik.uni-freiburg.de/publications/papers/schaefer18iros.pdf) [\[code\]](https://github.com/acschaefer/ple) 42 | 2. **A robust pose graph approach for city scale LiDAR mapping**, Sheng Yang, Xiaoling Zhu, Xing Nian, Lu Feng, Xiaozhi Qu and Teng Ma 43 | 3. **Dynamic Scaling Factors of Covariances for Accurate 3D Normal Distributions Transform Registration** , Hyunki Hong and B. H. Lee 44 | 4. **Integrating Deep Semantic Segmentation into 3D Point Cloud Registration** Anestis Zaganidis, Li Sun, Tom Duckett, Grzegorz Cielniak [\[pdf\]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8387438) 45 | 5. **LIMO Lidar-Monocular Visual Odometry**, Johannes Graeter, Alexander Wilczynski and Martin Lauer [\[pdf\]](https://arxiv.org/abs/1807.07524) [\[code\]](https://github.com/johannes-graeter/limo) 46 | 6. **LIPS LiDAR-Inertial 3D Plane SLAM**, Patrick Geneva, Kevin Eckenhoff, Yulin Yang and Guoquan Huang [\[pdf\]](https://www.researchgate.net/profile/Yulin_Yang3/publication/327514859_LIPS_LiDAR-Inertial_3D_Plane_SLAM/links/5b92ebdd299bf1473923ca77/LIPS-LiDAR-Inertial-3D-Plane-SLAM.pdf) [\[code\]](https://github.com/rpng/lips) 47 | 7. **PoseMap Lifelong, Multi-Environment 3D LiDAR Localization**, Philipp Egger, Paulo V K Borges, Gavin Catt, Andreas Pfrunder, Roland Siegwart, Renaud Dubé [\[pdf\]](https://research.csiro.au/robotics/wp-content/uploads/sites/96/2018/09/posemap_iros2018-10.pdf) [\[video1\]](https://youtu.be/BWxDRWdIpY) [\[video2\]](https://youtu.be/KSxuxDnfiko) 48 | 8. **Stabilize an Unsupervised Feature Learning for LiDAR-based Place Recognition**, Peng Yin, Lingyun Xu, Zhe Liu, Lu Li, Hadi Salman, Yuqing He, 49 | Weiliang Xu, Hesheng Wang and Howie Choset 50 | 9. **Stereo Camera Localization in 3D LiDAR Maps**, Youngji Kim, Jinyong Jeong and Ayoung Kim [\[video\]](https://www.youtube.com/watch?v=jdVno7qb3O0) 51 | 10. **LeGO-LOAM_ Lightweight and Ground-Optimized_Lidar Odometry and Mapping on Variable Terrain**, Tixiao Shan and Brendan Englot [\[pdf\]](https://github.com/RobustFieldAutonomyLab/LeGO-LOAM/blob/master/Shan_Englot_IROS_2018_Preprint.pdf) [\[code\]](https://github.com/RobustFieldAutonomyLab/LeGO-LOAM) [\[video\]](https://www.youtube.com/watch?v=O3tz_ftHV48) 52 | 11. **LiDAR and Camera Calibration using Motions Estimated by Sensor_Fusion Odometry**, Ryoichi Ishikawa, Takeshi Oishi and Katsushi Ikeuchi [\[pdf\]](https://arxiv.org/pdf/1804.05178.pdf) 53 | 12. **Scan Context: Egocentric Spatial Descriptor for Place Recognition within 3D Point Cloud Map**, Giseop Kim and Ayoung Kim 54 | 55 | ### Event Camera 56 | 57 | 1. **AsynchronousCornerDetectionandTrackingforEventCamerasinReal-Time**, Ignacio Alzugaray and Margarita Chli [\[pdf\]](https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/277131/RAL2018-camera-ready.pdf?sequence=1&isAllowed=y) [\[video\]](https://youtu.be/bKUAZ7IQcf0) 58 | 59 | ### Mapping 60 | 61 | 1. **A B-spline Mapping Framework for Long-Term Autonomous Operations**, Rômulo T. Rodrigues, A. Pedro Aguiar and António Pascoal [\[video\]](https://www.youtube.com/watch?v=Jnpo1qFP1m0) 62 | 2. **C-blox A Scalable and Consistent TSDF-based Dense Mapping Approach**, Alexander Millane, Zachary Taylor, Helen Oleynikova, Juan Nieto, Roland Siegwart, César Cadena [\[pdf\]](https://arxiv.org/pdf/1710.07242.pdf) [\[code\]](https://github.com/ethz-asl/c-blox) 63 | 3. **Efficient Long-term Mapping in Dynamic Environments**, Marı́a T. Lázaro, Roberto Capobianco and Giorgio Grisetti [\[code\]](https://gitlab.com/srrg-software/srrg_mapper2d) 64 | 4. **HMAPs – Hybrid Height-Voxel Maps for Environment Representation**, Luı́s Garrote, Cristiano Premebida, David Silva, Urbano J. Nunes 65 | 5. **Human-in-the-loop Augmented Mapping**, Abbas Sidaoui, Imad H. Elhajj, and Daniel Asmar 66 | 6. **Structured Skip List A Compact Data Structure for 3D Reconstruction**, Shi-Jie Li, Ming-Ming Cheng, Yun Liu, Shao-Ping Lu, YaHui Wang, Victor Adrian Prisacariu [\[pdf\]](http://www.shaopinglu.net/index.files/IROS2018.pdf) 67 | 68 | ### SLAM System 69 | 1. **ArthroSLAM: multi-sensor robust visual localization for minimally invasive orthopedic surgery**, Andres Marmol, Peter Corke, Thierry Peynot 70 | 2. **DynaSLAM Tracking, Mapping and Inpainting in Dynamic Scenes**, Berta Bescos, José M. Fácil, Javier Civera and José Neira [\[pdf\]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8421015) [\[video\]](https://youtu.be/EabI\_goFmQs) 71 | 3. **Improving Repeatability of Experiments by Automatic Evaluation of SLAM Algorithms**, Francesco Amigoni, Valerio Castelli, and Matteo Luperto [\[code\]](https://github.com/AIRLab-POLIMI/predictivebenchmarking) 72 | 4. **Indoor Mapping and Localization for Pedestrians using Opportunistic Sensing with Smartphones**, Qing Liang, Lujia Wang, Youfu Li and Ming Liu [\[video\]](https://www.youtube.com/watch?v=kQa3SwFiaAY) 73 | 5. **MIS-SLAM Real-time Large Scale Dense Deformable SLAM System in Minimal Invasive Surgery Based on Heterogeneous Computing**, Jingwei Song, Jun Wang, Liang Zhao, Shoudong Huang and Gamini Dissanayake [\[pdf\]](https://arxiv.org/pdf/1803.02009.pdf) 74 | 6. **Omnidirectional DSO Direct Sparse Odometry with Fisheye Cameras**, Hidenobu Matsuki, Lukas von Stumberg, Vladyslav Usenko, Jörg Stückler and Daniel Cremers [\[pdf\]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8410468) [\[video\]](https://www.youtube.com/watch?v=QQcIYCssp-c) 75 | 7. **OpenSeqSLAM2.0 An Open Source Toolbox for Visual Place Recognition Under Changing Conditions**, Ben Talbot, Sourav Garg, and Michael Milford [\[pdf\]](https://arxiv.org/pdf/1804.02156.pdf) [\[code\]](http://tiny.cc/openseqslam2) 76 | 8. **Probabilistic Dense Reconstruction from a Moving Camera**, Yonggen Ling, Kaixuan Wang and Shaojie Shen [\[code\]](https://github.com/ygling2008/probabilistic_mapping) [\[video\]](https://1drv.ms/v/s!ApzRxvwAxXqQmlW9ZOrp9hdA7ude) 77 | 9. **Robust Long-Term Registration of UAV Images of Crop Fields for Precision Agriculture**, Nived Chebrolu Thomas Läbe and Cyrill Stachniss [\[pdf\]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8392366) 78 | 10. **Semi-Supervised SLAM Leveraging Low-Cost Sensors on Underground Autonomous Vehicles for Position Tracking**, Adam Jacobson, Fan Zeng, David Smith, Nigel Boswell, Thierry Peynot and Michael Milford 79 | 11. **Towards Robust Visual Odometry with a Multi-Camera System**, Peidong Liu, Marcel Geppert, Lionel Heng, Torsten Sattler, Andreas Geiger and Marc Pollefeys [\[pdf\]](http://www.cvlibs.net/publications/Liu2018IROS.pdf) [\[code\]](https://cvg.ethz.ch/research/visual-odometry) 80 | 12. **Fast Cylinder and Plane Extraction from Depth Cameras for Visual_Odometry**, Pedro F. Proença and Yang Gao [\[pdf\]](https://arxiv.org/pdf/1803.02380.pdf) [\[code\]](https://github.com/pedropro/CAPE) [\[video\]](https://youtu.be/FPFPVwm_yq0) 81 | 13. **Geometric-based Line Segment Tracking for HDR Stereo Sequences**, Ruben Gomez-Ojeda, Javier Gonzalez-Jimenez [\[pdf\]](https://arxiv.org/pdf/1809.09368.pdf) [\[code\]](https://github.com/rubengooj/StVO-PL) 82 | 14. **Multimotion Visual Odometry (MVO): Simultaneous Estimation of Camera and Third-Party Motions**, Kevin M. Judd and Jonathan D. Gammell and Paul Newman [\[pdf\]](https://arxiv.org/pdf/1808.00274.pdf) 83 | 15. **Reliable fusion of black-box estimates of underwater localization**, Hendry Ferreira Chame, Matheus Machado dos Santos, Sı́lvia Silva da Costa Botelho [\[code\]](https://github.com/henferch/BAR-F) 84 | 16. **Stereo Visual Odometry and Semantics based Localization of Aerial_Robots in Indoor Environments**, Hriday Bavle, Stephan Manthe, Paloma de la Puente, 85 | Alejandro Rodriguez-Ramos, Carlos Sampedro, Pascual Campoy [\[video\]](https://vimeo.com/259349563) 86 | 87 | ### Backend 88 | 89 | 1. **LDSO Direct Sparse Odometry with Loop Closure**, Xiang Gao, Rui Wang, Nikolaus Demmel and Daniel Cremers [\[pdf\]](https://arxiv.org/pdf/1808.01111.pdf) [\[code\]](https://github.com/tum-vision/LDSO) [\[video\]](https://vision.in.tum.de/research/vslam/ldso) 90 | 2. **Predicting Objective Function Change in Pose-Graph Optimization**, Fang Bai, Teresa Vidal-Calleja, Shoudong Huang, and Rong Xiong 91 | 3. **Scan Similarity-based Pose Graph Construction Method for Graph SLAM**,Wonsok Yoo, Hanjun Kim, Hyunki Hong, and Beom H. Lee [\[pdf\]](http://s-space.snu.ac.kr/bitstream/10371/140701/1/000000150530.pdf) 92 | 4. **Submap-based Pose-graph Visual SLAM A Robust Visual Exploration and Localization System**, Weinan Chen, Lei Zhu, Yisheng Guan, C. Ronald Kube, Hong Zhang [\[pdf\]](https://arxiv.org/pdf/1807.01012.pdf) 93 | 5. **Virtual Occupancy Grid Map for Submap-based Pose Graph SLAM and Planning in 3D Environments**, Bing-Jui Ho, Paloma Sodhi, Pedro Teixeira, Ming Hsiao, Tushar Kusnur, and Michael Kaess [\[pdf\]](https://www.ri.cmu.edu/wp-content/uploads/2018/09/Ho18iros.pdf) 94 | 95 | ### Frontend 96 | 1. **A Combined RGB and Depth Deor for SLAM with Humanoids**, Rasha Sheikh, Stefan Oßwald and Maren Bennewitz [\[pdf\]](https://www.hrl.uni-bonn.de/papers/sheikh18iros.pdf) [\[code\]](https://github.com/ferasha/DLab) 97 | 2. **Good Feature Selection for Least Squares Pose Optimization in VOVSLAM**, Yipu Zhao and Patricio A. Vela 98 | 3. **HBST A Hamming Distance embedding Binary Search Tree for Feature-based Visual Place Recognition**, Dominik Schlegel and Giorgio Grisetti [\[pdf\]](https://arxiv.org/pdf/1802.09261.pdf) [\[code\]](http://www.gitlab.com/srrg-software/srrg_hbst) 99 | 4. **Keyframe-based Photometric Online Calibration and Color Correction**, Jan Quenzel, Jannis Horn, Sebastian Houben and Sven Behnke [\[pdf\]](https://www.ais.uni-bonn.de/papers/IROS_2018_Quenzel.pdf) [\[video\]](https://www.ais.uni-bonn.de/videos/IROS_2018_photometric_calibration/) 100 | 5. **Optimized Contrast Enhancements to Improve Robustness of Visual Tracking in a SLAM Relocalisation Context**, Xi Wang, Marc Christie, Eric Marchand [\[pdf\]](https://hal.inria.fr/hal-01852003/document) 101 | 6. **Robust Camera Pose Estimation via Consensus on Ray Bundle and Vector Field**, Haoang Li, Ji Zhao, Jean-Charles Bazin, Lei Luo, Junlin Wu and Jian Yao 102 | 7. **Unit Quaternion-based Parameterization for Point Features in Visual Navigation**, James Maley and Guoquan Huang 103 | 8. **Perspective Correcting Visual Odometry for Agile MAVs using a Pixel Processor Array**, Colin Greatwood, Laurie Bose, Thomas Richardson, Walterio Mayol-Cuevas, Jianing Chen, Stephen J. Carey and Piotr Dudek [\[pdf\]](https://drive.google.com/file/d/1SYBrDyg9iC2NhgRyadqyQm6C-lpxfafk/view) [\[video\]](https://events.infovaya.com/presentation?id=35473) 104 | 105 | 106 | ### Deep SLAM 107 | 108 | 1. **A Variational Feature Encoding Method of 3D Object for Probabilistic Semantic SLAM**, H. W. Yu and B. H. Lee [\[pdf\]](https://arxiv.org/pdf/1808.10180.pdf) 109 | 2. **Bayesian Information Recovery from CNN for Probabilistic Inference**, Dmitry Kopitkov and Vadim Indelman [\[pdf\]](https://www.researchgate.net/profile/Vadim_Indelman/publication/327704320_Bayesian_Information_Recovery_from_CNN_for_Probabilistic_Inference/links/5ba002d9a6fdccd3cb5ee5d8/Bayesian-Information-Recovery-from-CNN-for-Probabilistic-Inference.pdf) 110 | 3. **DS-SLAM A Semantic Visual SLAM towards Dynamic Environments**, Chao Yu, Zuxin Liu, Xin-Jun Liu, Fugui Xie, Yi Yang, Qi Wei, Qiao Fei [\[pdf\]](https://arxiv.org/pdf/1809.08379.pdf) 111 | 4. **Fast and Accurate Semantic Mapping through Geometric-based Incremental Segmentation**, Yoshikatsu Nakajima, Keisuke Tateno, Federico Tombari and Hideo Saito [\[pdf\]](https://arxiv.org/pdf/1803.02784.pdf) 112 | 5. **Integrating Deep Semantic Segmentation into 3D Point Cloud Registration**, Anestis Zaganidis, LiSun, Tom Duckett, and Grzegorz Cielniak [\[pdf\]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8387438) 113 | 6. **Learning monocular visual odometry with dense 3D mapping from dense 3D flow**, Cheng Zhao, Li Sun, Pulak Purkait, Tom Duckett and Rustam Stolkin [\[pdf\]](https://arxiv.org/pdf/1803.02286.pdf) 114 | 7. **Localization of Classified Objects in SLAM using Nonparametric Statistics and Clustering**, Asif Iqbal 1 and Nicholas R. Gans 115 | 8. **Pose Estimation and Map Formation with Spiking Neural Networks towards Neuromorphic SLAM**, Raphaela Kreiser, Panin Pienroj, Alpha Renner, and Yulia Sandamirskaya [\[pdf\]](http://www.sandamirskaya.eu/resources/KreiserEtAl_2018iros.pdf) 116 | 9. **Robust Exploration with Multiple Hypothesis Data Association**, Jinkun Wang and Brendan Englot [\[pdf\]](http://personal.stevens.edu/~benglot/Wang_Englot_IROS_2018_Preprint.pdf) 117 | 10. **Semantic Monocular SLAM for Highly Dynamic Environments**, Nikolas Brasch, Aljaz Bozic, Joe Lallemand, Federico Tombari 118 | 11. **Unsupervised Odometry and Depth Learning for Endoscopic Capsule Robots**, Mehmet Turan, Evin Pinar Ornek, Nail Ibrahimli, Can Giracoglu, Yasin Almalioglu,Mehmet Fatih Yanik, and Metin Sitti [\[pdf\]](https://arxiv.org/pdf/1803.01047.pdf) 119 | -------------------------------------------------------------------------------- /_config.yml: -------------------------------------------------------------------------------- 1 | theme: jekyll-theme-slate -------------------------------------------------------------------------------- /标题图.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/mengyuest/iros2018-slam-papers/b1069e832386fb254cb9b960ab0109cd31bf8bfd/标题图.JPG --------------------------------------------------------------------------------