Object-centric Reconstruction and Tracking of Dynamic Unknown Objects using 3D Gaussian Splatting
University of Luxembourg（卢森堡大学）；Redwire Space Europe（雷德维尔欧洲航天公司）；Interdisciplinary Centre for Security, Reliability and Trust (SnT)（安全、可靠性与跨学科信任中心（SnT））
Kuldeep R Barad, Antoine Richard, Jan Dentler, Miguel Olivares-Mendez, Carol Martinez
备注：
Accepted at IEEE International Conference on Space Robotics 2024
发表信息：
2024 International Conference on Space Robotics (iSpaRo), Luxembourg, 2024, pp. 202-209
Generalizable perception is one of the pillars of high-level autonomy in space robotics. Estimating the structure and motion of unknown objects in dynamic environments is fundamental for such autonomous systems. Traditionally, the solutions have relied on prior knowledge of target objects, multiple disparate representations, or low-fidelity outputs unsuitable for robotic operations. This work proposes a novel approach to incrementally reconstruct and track a dynamic unknown object using a unified representation -- a set of 3D Gaussian blobs that describe its geometry and appearance. The differentiable 3D Gaussian Splatting framework is adapted to a dynamic object-centric setting. The input to the pipeline is a sequential set of RGB-D images. 3D reconstruction and 6-DoF pose tracking tasks are tackled using first-order gradient-based optimization. The formulation is simple, requires no pre-training, assumes no prior knowledge of the object or its motion, and is suitable for online applications. The proposed approach is validated on a dataset of 10 unknown spacecraft of diverse geometry and texture under arbitrary relative motion. The experiments demonstrate successful 3D reconstruction and accurate 6-DoF tracking of the target object in proximity operations over a short to medium duration. The causes of tracking drift are discussed and potential solutions are outlined.
CubifyGS: Object-Centric 3D Gaussian Splatting for Lifelong Dynamic Scene Maintenance
School of Automation, Beijing Institute of Technology, Beijing, China（北京理工大学自动化学院，北京，中国）；Guangzhou Saite Intelligent Technology Co., Ltd.（广州赛泰智能科技有限公司）
DLO-Splatting: Tracking Deformable Linear Objects Using 3D Gaussian Splatting
Department of Aerospace Engineering and the Coordinated Science Laboratory at the University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校航空航天工程系及协调科学实验室）；Division of Robotics, Perception and Learning at KTH Royal Institute of Technology（皇家理工学院机器人、感知与学习 division）；NASA Ames Research Center（NASA阿姆斯研究中心）
EGS-SLAM: RGB-D Gaussian Splatting SLAM with Events
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore（南洋理工大学电子与电气工程学院）；School of Instrumentation and Optoelectronics Engineering, Beihang University, Beijing, China（北京航空航天大学仪器与光电工程学院）
本文提出 EGS-SLAM 框架，通过融合事件数据与 RGB-D 输入并建模相机连续曝光轨迹，有效解决运动模糊问题，实现了高精度的稳健跟踪与高保真 3D 高斯泼溅重建。
Advancing Dense Endoscopic Reconstruction with Gaussian Splatting-driven Surface Normal-aware Tracking and Mapping
The Chinese University of Hong Kong (CUHK)（香港中文大学）；CUHK Shenzhen Research Institute（香港中文大学深圳研究院）；Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences（中国科学院香港创新研究院）；Qilu Hospital of Shandong University（山东大学齐鲁医院）
Robust Gaussian Splatting SLAM by Leveraging Loop Closure
School of Communication Engineering, Hangzhou Dianzi University（杭州电子科技大学通信工程学院）；Lishui Institute of Hangzhou Dianzi University（杭州电子科技大学丽水研究院）；School of Automation, Hangzhou Dianzi University（杭州电子科技大学自动化学院）；Faculty of Applied Sciences, Macao Polytechnic University（澳门理工大学应用科学学院）；School of Electrical and Electronics Engineering, Nanyang Technological University（南洋理工大学电气与电子工程学院）；School of Software, Tsinghua University（清华大学软件学院）；Technical University of Munich（慕尼黑工业大学）
GARAD-SLAM: 3D GAussian splatting for Real-time Anti Dynamic SLAM
School of Information and Communication Engineering, Dalian University of Technology（大连理工大学信息与通信工程学院）；School of Aeronautics and Astronautics, Sun Yat-sen University（中山大学航空航天学院）；Faculty of Science and Technology, University of Macau（澳门大学科技学院）
GeoGS-SLAM: Online Monocular Reconstruction Using Gaussian Splatting with Geometric Priors
State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University（工业控制技术国家重点实验室，浙江大学控制科学与工程学院）；Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province（浙江省协同感知与自主无人系统重点实验室）
SemGauss-SLAM: Dense Semantic Gaussian Splatting SLAM
School of Automation and Intelligent Sensing, Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai Jiao Tong University, Shanghai（自动化与智能感知学院、系统控制与信息处理重点实验室、中华人民共和国教育部、上海交通大学、上海）；University of Cambridge, United Kingdom（剑桥大学、英国）
Wuhan University（武汉大学）；School of Computer Science（计算机学院）；School of Electronic Information（电子信息学院）；School of Artificial Intelligence（人工智能学院）；National Engineering Research Center for Multimedia Software（多媒体软件国家工程研究中心）；Institute for Math & AI（数学与人工智能研究所）
Instrument-Splatting++: Towards Controllable Surgical Instrument Digital Twin Using Gaussian Splatting
Department of Biomedical Engineering, National University of Singapore (NUS)（生物医学工程系，新加坡国立大学）；Department of Electrical and Computer Engineering, The University of British Columbia（电气与计算机工程系，不列颠哥伦比亚大学）
RoGER-SLAM: A Robust Gaussian Splatting SLAM System for Noisy and Low-light Environment Resilience
College of Electronic and Information Engineering, Tongji University（同济大学电子与信息工程学院）；Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University（同济大学智能自主系统研究所）；Chair of Human-Machine Communication, Technical University of Munich（慕尼黑技术大学人机通信教授职位）；Professorship of Autonomous Vehicle Systems, Technical University of Munich（慕尼黑技术大学自动驾驶系统教授职位）
