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collecting some new ideas for slam (Semantic, 3DGS, BEV, Nav, LLM, Multi-session) and will update this repo weekly, for both engineering and academic usings.

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awesome-and-novel-works-in-slam Awesome

This repo contains a mostly cutting edge (new derives from old) list of awesome and novel works in slam

If you find this repository useful, please consider STARing this list. Feel free to share this list with others! More comments will be found below, yet just opinions of mine. Make slamer great again.

Overview

3DGS/EVER

Follow [Jiheng Yang] for more information on NeRF/3DGS/EVER, He will update news weekly, best Chinese community for NeRF/3DGS, I will do supplement when I have time.

Follow [ai kwea] for more practical experience on NeRF, I will do supplement when I have time.

Follow [Chongjie Ye] for more practical experience on 3DGS, I will do supplement when I have time.

  • Gaussian Splatting: "3D Gaussian Splatting for Real-Time Radiance Field Rendering", ACM Transactions on Graphics 2023. [Paper] [Code]

  • Neural-Sim: "Learning to Generate Training Data with NeRF", ECCV 2022. [Paper] [Code] [Webpage]

  • iNeRF: "Inverting Neural Radiance Fields for Pose Estimation", IROS, 2021. [Paper] [Code] [Website] [Dataset]

  • iMAP: "Implicit Mapping and Positioning in Real-Time", ICCV, 2021. [Paper] [Code]

  • SHINE-Mapping: "Large-Scale 3D Mapping Using Sparse Hierarchical Implicit Neural Representations", ICRA, 2023. [Paper] [Code]

  • H2-Mapping: "Real-time Dense Mapping Using Hierarchical Hybrid Representation", RA-L, 2023. [Paper] [Code]

  • LATITUDE: Robotic Global Localization with Truncated Dynamic Low-pass Filter in City-scale NeRF, ICRA, 2023. [Paper] [Code]

  • NeuSE: "Neural SE(3)-Equivariant Embedding for Consistent Spatial Understanding with Objects", arXiv. [Paper] [Code]

  • ObjectFusion: "Accurate object-level SLAM with neural object priors", Graphical Models, 2022. [Paper]

  • NDF_Change: "Robust Change Detection Based on Neural Descriptor Fields", IROS, 2022. [Paper]

  • LNDF: "Local Neural Descriptor Fields: Locally Conditioned Object Representations for Manipulation", ICRA, 2023. [Paper] [Webpage]

  • NeRF-LOAM: Neural Implicit Representation for Large-Scale Incremental LiDAR Odometry and Mapping, arXiv. [Paper] [Code]

  • "Implicit Map Augmentation for Relocalization", ECCV Workshop, 2022. [Paper]

  • Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAM, CVPR, 2023. [Paper] [Website]

  • Neural Implicit Dense Semantic SLAM, arXiv, 2023. [Paper]

  • NeRF-Navigation: "Vision-Only Robot Navigation in a Neural Radiance World", ICRA, 2022. [Paper] [Code] [Website]

  • ESDF: "Sampling-free obstacle gradients and reactive planning in Neural Radiance Fields", arXiv. [Paper]

  • GS-LIVOM: "Real-time Gaussian Splatting Assisted LiDAR-Inertial-Visual Odometry and Dense Mappings", arXiv2024. [Code]

v2x

Follow [Siheng Chen] for more information on V2X Perception, I will do supplement when I have time.

Follow [Runsheng Xu] for more information on V2X Perception, I will do supplement when I have time.

  • HighwayEnv: "An Environment for Autonomous Driving Decision-Making", GitHub. [Code]

  • OpenLane-V2: "The World's First Perception and Reasoning Benchmark for Scene Structure in Autonomous Driving.", GitHub. [Code]

semantic

  • OPen3d: "A Modern Library for 3D Data Processing", arxiv. [Paper] [Code]

  • SuMa++: "SuMa++: Efficient LiDAR-based Semantic SLAM", IEEE/RSJ International Conference on Intelligent Robots and Systems 2019. [Paper] [Code]

  • Khronos: "Khronos: A Unified Approach for Spatio-Temporal Metric-Semantic SLAM in Dynamic Environments", Robotics: Science and Systems. [Paper] [Code]

novelcv

  • UniDistill: "A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird's-Eye View", Github. [Code]

largemodel

  • DriveLikeAHuman: "Rethinking Autonomous Driving with Large Language Models", CVPR, 2023. [Code]

  • learnLLM[Code]

  • ReAct: Synergizing Reasoning and Acting in Language Models[Code]

  • GraphRag[Code]

leaders

Industries and the off-campus

UK

  • Oxford Control Group [Homepage]

  • Oxford Dynamic Robot Systems Group [Homepage]

  • Imperial College London Dyson Robotics Laboratory [Homepage]

  • UCL CDT in Foundational AI [Homepage]

  • UCL Robot Perception and Learning Lab [Homepage]

  • School of Informatics University of Edinburgh [Homepage]

Europe

  • ETHZ Autonomous Systems Lab [Homepage]

  • ETHZ Robotic Systems Lab [Homepage]

  • ETHZ Computer-Vision-and-Geometry-Lab [Homepage]

  • ETHZ Visual Intelligence and Systems Group [Homepage]

  • ETHZ University of Cyprus Vision for Robotics Lab [Homepage]

  • ETHZ Learning and Adaptive Systems Group [Homepage]

  • EPFL CV LAB [Homepage]

  • TUM-Institue-of-Auotomative-Technology [Homepage]

  • TUM-Computer-Vision-Group [Homepage]

  • TUM Smart Robotics Lab [Homepage]

  • Flight Robotics and Perception Group (FRPG) [Homepage]

  • Heidelberg Computer Vision and Learning Lab [Homepage]

  • UFR Robot Learning [Homepage]

  • University of Tübingen [Homepage]

  • Bonn Photogrammetry Robotics [Homepage]

  • Karlsruhe Institute of Technology Institute of Measurement and Control Systems [Homepage]

  • IGMR - RWTH Aachen University [Homepage]

  • RWTH Aachen Institute of Automatic Control [Homepage]

  • RWTH Aachen Institut für Kraftfahrzeuge ika [Homepage]

  • Albert-Ludwigs-Universität Freiburg Robot Learning Lab [Homepage]

  • KTH Robotics Perception and Learning [Homepage]

  • University of Turku Turku Intelligent Embedded and Robotic Systems Lab [Homepage]

  • NMBU Robotics [Homepage]

  • TU Delft 3D geoinformation research group [Homepage]

  • TU Delft Intelligent Vehicles [Homepage]

  • Poznan University of Technology Mobile Robots Lab [Homepage]

  • Sapienza University of Rome Robots Vision and Perception [Homepage]

  • Vision for Robotics and Autonomous Systems Czech Technical University in Prague (CTU) [Homepage]

Notrh America

  • Stanford Autonomous Systems Lab [Homepage]

  • Stanford Robotics Embodied Artificial Intelligence Lab REAL [Homepage]

  • Stanford Vision and Learning Lab [Homepage]

  • Stanford Computational Vision and Geometry Lab [Homepage]

  • Stanford Center for Research on Foundation Models [Homepage]

  • MIT-SPARKs [Homepage]

  • MIT Driverless Perception Team [Homepage]

  • MIT CSAIL Computer Vision [Homepage]

  • MIT's Marine Robotics Group [Homepage]

  • MIT HAN Lab [Homepage]

  • MIT Aerospace Controls Laboratory [Homepage]

  • CMU Robotics Institute AirLab [Homepage]

  • CMU Robotic Exploration Lab [Homepage]

  • CMU Robot Perception Lab [Homepage]

  • Learning and Control for Agile Robotics Lab at CMU [Homepage]

  • Princeton Computational Imaging [Homepage]

  • UPenn Perception Action Learning Group [Homepage]

  • UPenn Kumar Robotics [Homepage]

  • UCB Model Predictive Control Laboratory [Homepage]

  • Berkeley Automation Lab [Homepage]

  • UCLA Verifiable & Control-Theoretic Robotics Laboratory [Homepage]

  • UCLA Mobility Lab [Homepage]

  • UCSD Existential Robotics Lab [Homepage]

  • Umich Ford Center for Autonomous Vehicles FCAV [Homepage]

  • Umich The Autonomous Robotic Manipulation Lab studies motion planning manipulation human-robot collaboration [Homepage]

  • Umich Dynamic Legged Locomotion Robotics Lab [Homepage]

  • NYU AI4CE Lab [Homepage]

  • GaTech BORG Lab [Homepage]

  • GaTech Intelligent Vision and Automation Laboratory IVA Lab [Homepage]

  • Texas Austin Autonomous Mobile Robotics Laboratory [Homepage]

  • University of Delaware Robot Perception Navigation Group RPNG [Homepage]

  • Virginia Tech Transportation Institute [Homepage]

  • SIT Robust Field Autonomy Lab [Homepage]

  • University at Buffalo Spatial AI & Robotics Lab [Homepage]

  • UWaterloo CL2 [Homepage]

  • UBC Computer Vision Group [Homepage]

  • École Polytechnique de Montréal Making Innovative Space Technology Lab [Homepage]

Asia

  • Yonsei Computational Intelligence Laboratory [Homepage]

  • SNU RPM [Homepage]

  • KAIST Urban Robotics Lab [Homepage]

  • KAIST Cognitive Learning for Vision and Robotics CLVR lab [Homepage]

  • Japan National Institute of Advanced Industrial Science and Technology [Homepage]

  • Japan Nagoya [Homepage]

  • CUHK OpenMMLab [Homepage]

  • HKUST Aerial Robotics Group [Homepage]

  • HKU Mars Lab [Homepage]

  • City University of Hong Kong MetaSLAM [Homepage]

  • HK PolyU Visual Learning and Reasoning Group [Homepage]

  • NTNU Autonomous Robots Lab [Homepage]

  • Tsinghua IIIS MARS Lab [Homepage]

  • Tsinghua Institute for AI Industry Research [Homepage]

  • SJTU Vision and Intelligent System Group [Homepage]

  • SJTU Intelligent Robotics and Machine Vision Lab [Homepage]

  • ZJU Advanced-Perception-on-Robotics-and-Intelligent-Learning-Lab [Homepage]

  • ZJU CAD CG [Homepage]

  • ZJU Advanced Intelligent Machines AIM [Homepage]

  • ZJU Robotics Lab [Homepage]

  • ZJU FAST Lab [Homepage]

  • Fudan Zhang Vision Group [Homepage]

  • Tongji Intelligent Electric Vehicle Research Group [Homepage]

  • Tongji Intelligent Sensing Perception and Computing Group [Homepage]

  • NUDT NuBot [Homepage]

  • HUST EIC Vision Lab [Homepage]

  • ShanghaiTech Vision and Intelligent Perception Lab [Homepage]

  • HITSZ nROS-Lab [Homepage]

  • GAP-LAB-CUHK-SZ [Homepage]

  • Westlake University Audio Signal and Information Processing Lab [Homepage]

  • Wuhan University Urban Spatial Intelligence Research Group at LIESMARS [Homepage]

  • Wuhan University Integrated and Intelligent Navigation Group [Homepage]

  • WHU GREAT (GNSS+ Research, Application and Teaching) group [Homepage]

  • SYSU STAR Smart Aerial Robotics Group [Homepage]

  • SYSU RAPID Lab [Homepage]

  • SYSU Pengyu Team [Homepage]

  • NEU REAL [Homepage]

  • Israel Autonomous Navigation and Sensor Fusion Lab [Homepage]

Australia

  • CSIRORobotics Brisbane, Queensland, Australia [Homepage]

  • Robotics Institute, University of Technology Sydney [Homepage]

Find more on this link in case of u r looking for PhD positions[I] [II].

Journals

Conferences

  • Mar. RSS Robotics: Science and Systems [Registeration]

  • Nov. CVPR IEEE Conference on Computer Vision and Pattern Recognition [Registeration]

  • Sept. ICRA IEEE International Conference on Robotics and Automation [Registeration]

  • Mar. IROS IEEE/RSJ lnternational Conference onlntelligent Robots and Systems [Registeration]

  • Mar. ICCV International Conference on Computer Vision [Registeration]

  • Mar. ECCV European Conference on Computer Vision [Registeration]

  • Jan. SIGGRAPH Special Interest Group for Computer GRAPHICS [Registeration]

  • Jul. CoRL Conference on Robot Learning [Registeration]

  • Sept. ICLR International Conference on Learning Representations [Registeration]

Datasets

find more in paperwithcode

Competition

Practice makes perfect, though lack of innovation.

  • ICRA 2023 Robodepth [Link]
  • ICRA 2024 RoboDrive [Link]
  • ICRA 2023 Sim2Real [Link]

Tools

Libs:

NeRF/3DGS:

Calibration:

Evaluation:

Communication:

  • Message Queuing Telemetry Transport [Video]

  • Hypertext Transfer Protocol Secure [Video]

  • Controller Area Network [Video]

Deep Learning Framework:

Sim (experienced software, not toys from paper)

BuySensors

Multi-sensors:RGB, RGBD, Infrared, Polarization, Event-based(Future), Motion, Capture(GT), 2D Spinning LiDAR, 3D Spinning LiDAR, 3D Solid-State LiDAR, 4D High Resolution Radar(Future), mmWave Radar, UWB, RTK(GT), Wheel Odom, IMU, Ultrasonic Sensor.

FindIntern

For bridging college and society, mainly base in Shanghai, Beijing, Hangzhou, Suzhou, Canton, Shenzhen, HongKong

Shanghai: AI Lab, DiDi, Horizon, Li Auto, BOSCH, Huawei, SenseTime,

Beijing: Xiaomi, Baidu, Pony.ai,

Hangzhou: Unitree, Damo,

Suzhou: Momenta,

Canton: ZhuoYu, WeRide, Xiaopeng,

interview experience like Find More

BTW, RA/TA Opportunities：

CMU AirLab

CityU MetaSLAM

ETH-RSS

WeMedia

Follow [XueLingFeiHua] for general understanding of sensors used by autonomous vehicle, I will do supplement when I have time.

WhySDMap

For autonomous driving vechile and outdoor robotics, use more light-weight map instead of no map, specifically more like maplite [demo]

Especially for indoor environments, the prior is BIM [BIM]

  • RoadNet: "Translating Images to Road Network: A Non-Autoregressive Sequence-to-Sequence Approach", ICCV 2023 (Oral). [Paper] [Code]

    Follow [TUMFTM] for more information on HDMap & SDMap aided localization, I will do supplement when I have time.

    Follow [Tong Qin] for more information on SDMap aided localization, I will do supplement when I have time.

    Follow [Yujiao Shi] and [tudelft-iv] for more information on Satellite images aided localization, I will do supplement when I have time.

WhyTraversability

For all terrain navigation, because We're tired of filtering ground points...

  • MonoForce: "MonoForce: Self-supervised Learning of Physics-aware Model for Predicting Robot-terrain Interaction", arXiv 2022. [Paper] [Code]

  • TML: "A Global Traversability Mapping Library easily integratable with any SLAM System". [Code]

  • TMMP: "Bayesian Generalized Kernel Inference for Terrain Traversability Mapping", the 2nd Annual Conference on Robot Learning. [Code]

  • STEPP: "STEPP: Semantic Traversability Estimation using Pose Projected features", not yet. [Code]

  • HFHWC: "Autonomous Driving in Unstructured Environments: How Far Have We Come?", [Code]

  • EcSemMap: "Uncertainty-aware Evidential Bayesian Semantic Mapping (EBS)", [Code]

  • LoD: "Learning-on-the-Drive: Self-supervised Adaptive Long-range Perception for High-speed Offroad Driving", [Paper]

WhyLongTerm

For multi-session mapping and updating (change detection), dynamic objects filter.

  • KISS-Matcher: "KISS-Matcher: Fast and Robust Point Cloud Registration Revisited", arxiv 2024. [Paper] [Code]

  • G3Reg: "Pyramid Semantic Graph-based Global Point Cloud Registration with Low Overlap", IEEE/RSJ International Conference on Intelligent Robots and Systems 2023. [Code]

  • DeepPointMap: "DeepPointMap: Advancing LiDAR SLAM with Unified Neural Descriptors", AAAI Conference on Artificial Intelligence 2024. [Code]

  • GLoc3D: "Global Localization in Large-scale Point Clouds via Roll-pitch-yaw Invariant Place Recognition and Low-overlap Global Registration", *IEEE Transactions on Circuits and Systems for Video Technology *. [Code]

  • maplalb2.0: "maplab 2.0 – A Modular and Multi-Modal Mapping Framework", IEEE Robotics and Automation Letters. [Code]

  • MR-SLAM: "Disco: Differentiable scan context with orientation", IEEE Robotics and Automation Letters. [Code]

  • MS-Mapping: "MS-Mapping: An Uncertainty-Aware Large-Scale Multi-Session LiDAR Mapping System", arxiv 2024. [Paper] [Code]

  • NF-Atlas: "Multi-Volume Neural Feature Fields for Large Scale LiDAR Mapping", IEEE Robotics and Automation Letters 2023. [Paper] [Code]

  • DiSCo-SLAM: "DiSCo-SLAM: Distributed Scan Context-Enabled Multi-Robot LiDAR SLAM With Two-Stage Global-Local Graph Optimization", IEEE International Conference on Robotics and Automation 2022. [Paper] [Code]

  • imesa: "{iMESA}: Incremental Distributed Optimization for Collaborative Simultaneous Localization and Mapping", Robotics: Science and Systems 2024. [Paper] [Code]

  • DCL-SLAM: "Swarm-lio: Decentralized swarm lidar-inertial odometry", IEEE International Conference on Robotics and Automation 2023. [Paper] [Code]

  • BlockMap: "Block-Map-Based Localization in Large-Scale Environment", IEEE International Conference on Robotics and Automation 2024. [Paper] [Code]

  • SLIM: "SLIM: Scalable and Lightweight LiDAR Mapping in Urban Environments", arxiv maybe tro 2024. [Paper] [Code]

    Follow [Ji Zhang] for more information on Robust Navigation, I will do supplement when I have time.

    Follow [Xiang Gao] for more information on SLAM, I will do supplement when I have time.

    Follow [Tong Qin] for more information on V-SLAM, I will do supplement when I have time.

    Follow [Gisbi Kim] for more information on Map Maintaining, I will do supplement when I have time.

    Follow [Kin Zhang] for more information on Dynamic Objects Removing, I will do supplement when I have time.

    Follow [Zhijian Qiao] for more information on Multi-Session Mapping, I will do supplement when I have time.

    Follow [koide] for more information on Life-Long LiDAR Mapping, I will do supplement when I have time.

Citation

If you find this repository useful, please consider citing this repo:

@misc{runjtu2024slamrepo,
    title = {awesome-and-novel-works-in-slam},
    author = {Runheng Zuo},
    howpublished = {\url{https://github.com/runjtu/awesome-and-novel-works-in-slam}},
    year = {2024},
    note = "[Online; accessed 04-October-2024]"
}

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collecting some new ideas for slam (Semantic, 3DGS, BEV, Nav, LLM, Multi-session) and will update this repo weekly, for both engineering and academic usings.

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