Latest Spatial AI & SLAM Research Papers

The newest Spatial AI & SLAM papers from across the field — arXiv, NeurIPS, CVPR, Nature, and more — refreshed daily and ranked by relevance. Distill AI tracks Spatial AI & SLAM so you don’t have to: get the standout work delivered to your inbox every morning, with 2-sentence summaries and the option to chat with any paper.

Recent papers

• GLAM-SLAM: Real-time Gaussian Large-scale Mapping via Flow Densification and Spatial Decomposition
  Panagiotis Mermigkas, Argyris Manetas, Petros Maragos · arXiv · Jul 23, 2026

  Existing Gaussian-splatting-based monocular Simultaneous Localization and Mapping (SLAM) systems are either tailored to short sequences, are not real-time, or suffer from prohibitive GPU memory requirements, limiting their applicability in …

• DINS-IO: Learned Inertial Odometry via Differentiable INS Consistency
  Hao Qiao, Yan Wang, Jian Kuang, Xiaoji Niu · arXiv · Jul 22, 2026

  The training of learned inertial odometry depends on dense, high-precision position ground truth from motion capture, visual-inertial odometry or SLAM, which is costly and hard to acquire at scale. We propose DINS-IO, which learns inertial …

• Cognitive Dual-Process Planning for Autonomous Driving with Structured Scene Knowledge and Verifiable Reasoning-Action Consistency
  Zhongyao Yang, Haoyu Li, Yu Yan, Zhuangxuan Yu et al. · arXiv · Jul 21, 2026

  High-level planning for autonomous driving is a knowledge-intensive engineering decision task that requires accurate scene understanding, timely inference, and internally consistent action selection. Vision-language models (VLMs) can make i…

• Hydra++: Real-Time Hierarchical 3D Scene Graph Construction With Object-Level Shape Estimation
  Hyungtae Lim, Nathan Hughes, Xihang Yu, Ruihan Xu et al. · arXiv · Jul 10, 2026

  3D scene graphs provide a hierarchical abstraction of environments by encoding spatial entities, such as objects and places, and their relationships. However, existing scene graph systems model object geometry coarsely, relying on partial p…

• GeoGS-SLAM: Geometry-Only Gaussian Splatting for Dense Monocular SLAM
  Lipu Zhou, Yaoyun Kang, Junxiang Pang, Shengkai Sun et al. · arXiv · Jul 8, 2026

  Dense visual SLAM is a fundamental problem in robotics. Recent advances in 3DGS have demonstrated its potential for dense SLAM. Existing 3DGS frameworks focus on both appearance and geometry modeling. However, scene geometry is typically mo…

• PLED-VINS: A Point-Line Event-Based Visual Inertial SLAM for Dynamic Environments
  Seunghun Lee, Jihun Nam, Dong-Uk Seo, Hyun Myung · arXiv · Jul 8, 2026

  Dynamic environments remain a fundamental challenge for visual SLAM, where unreliable observations from moving objects and rapid motion degrade state estimation accuracy. Although event cameras preserve fine-grained spatio-temporal informat…

• Hilti-Trimble-Oxford Dataset: 360 Visual-Inertial Benchmark with Floor Plan Priors for SLAM and Localization
  Samuele Centanni, Yuhao Zhang, Yifu Tao, Julien Kindle et al. · arXiv · Jul 7, 2026

  Automated progress monitoring on construction sites is an active area of research and development. Robot and human-carried mapping systems have been developed to build 3D maps of building and infrastructure projects. While LiDAR-based mappi…

• From Foundation to Application: Improving VLA Models in Practice
  Wei Wu, Fangjing Wang, Fan Lu, He Sun et al. · arXiv · Jul 7, 2026

  Despite recent progress of VLA foundation models, the disparity between laboratory conditions and real-world applications continues to impede their practical implementation. To bridge this gap, we present LingBot-VLA 2.0, which advances Lin…

• A Stereo Visual SLAM System Using Object-Level Motion Estimation and Geometric Filtering Based on Cross Disparity
  Sujan Kumar Dhali, Bhaskar Dasgupta · arXiv · Jul 2, 2026

  This paper presents OCD SLAM, a dynamic stereo visual SLAM framework that extends ORB-SLAM2 by jointly addressing dynamic objects and dynamic features in the scene. Usual visual SLAM systems operating in dynamic environments often fail in t…

• Privacy-Preserving Depth-Only Open-Vocabulary 3D Semantic Segmentation Via Uncertainty-Guided Test-Time Optimization
  Xuying Huang, Sicong Pan, Maren Bennewitz · arXiv · Jul 1, 2026

  Privacy-preserving perception is a critical requirement for deploying 3D scene understanding systems in real-world indoor environments, yet it remains underexplored in open-vocabulary 3D semantic segmentation. Existing methods typically rel…

• Self-supervised Geometry Reasoning for LiDAR Simultaneous Localization and Mapping
  Jiwoo Kim, Jinwoo Lee, Woojae Shin, Giseop Kim et al. · arXiv · Jun 29, 2026

  LiDAR simultaneous localization and mapping (SLAM) relies on local geometric quantities such as covariances, correspondences, and surface structures. However, most existing pipelines rely on hand-crafted estimates of local geometry and use …

• LXD-SLAM: LiDAR+X Dense SLAM with $\sum_{i=0}^{5}C_5^i$ Configurable Sensor Combinations
  Zhong Wang, Lin Zhang, Linfei Li, Ying Shen et al. · arXiv · Jun 26, 2026

  Simultaneous Localization and Mapping (SLAM) is essential for autonomous systems, yet achieving reliable, globally consistent pose estimation and dense mapping in complex environments remains challenging due to geometric degeneracy and sens…

• RoboAtlas: Contextual Active SLAM
  Alexander Schperberg, Shivam K. Panda, Abraham P. Vinod, M. K. Jawed et al. · arXiv · Jun 24, 2026

  We present RoboAtlas, a contextual Active SLAM framework that adaptively balances geometric exploration and semantic reasoning using a scalable 3D semantic mapping system, OpenRoboVox. RoboAtlas integrates frontier exploration, global seman…

• DSP-SLAM++: A Unified Framework for Multi-Class, High-Fidelity Object SLAM in the Wild
  Ahmad Kourani, Ghina Daoud, Daniel Asmar, Imad Elhajj · arXiv · Jun 24, 2026

  Existing object-aware SLAM systems force a trade-off between real-time performance, multi-class support, and the generation of high-fidelity, semantically coherent object models. To address this trade-off, we present DSP-SLAM++, which exten…

• Vision-Language Model Reasoning for Contextual Semantic Mapping in Intralogistics
  Marvin Rüdt, Hao Pang, Constantin Enke, Zäzilia Seibold et al. · arXiv · Jun 23, 2026

  Autonomous mobile robots operating in intralogistics environments rely on geometric maps for localization and navigation, but lack semantic understanding of objects and their contextual properties. We present a contextual semantic mapping p…

• Decentralized Pose Graph Riemannian Optimization for Object-based Multi-Robot SLAM
  Yixian Zhao, Yan Huang, Yang Xu, Liang Li et al. · arXiv · Jun 23, 2026

  Pose graph optimization (PGO) is a key back-end component for state estimation in networked multi-robot simultaneous localization and mapping (SLAM). In object-based multi-robot SLAM, the problem becomes more tightly coupled because robots …

• Situated Perception: Spatial AI-Enabled Scene- and Object-level Localisation for Mobile Robotic Assembly
  Begüm Saral, Hanzhi Chen, Stefan Leutenegger, K. Dörfler · Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC) · Jun 22, 2026
• OneCanvas: 3D Scene Understanding via Panoramic Reprojection
  Bartłomiej Baranowski, Dave Zhenyu Chen, Matthias Nießner · arXiv · Jun 17, 2026

  Existing approaches to 3D scene understanding in Vision-Language Models (VLMs) either rely on complex, model-specific geometry encoders or large training budgets in pursuit of spatial reasoning. Instead, OneCanvas aggregates patch features …

• SGM-SLAM: Scene Graph Matching for Data-Efficient Distributed SLAM
  Yewei Huang, Tixiao Shan, Abhinav Rajvanshi, Niluthpol Chowdhury Mithun et al. · arXiv · Jun 15, 2026

  We introduce a data-efficient distributed Simultaneous Localization and Mapping (SLAM) framework designed for a team of robots equipped with LiDAR, cameras, and inertial sensors. Our framework uses scene graph matching to identify inter-rob…

• A Unified Spatial AI Framework for Cross-Domain Tissue-State Analysis in Trauma, Oral, and Cardiovascular Pathology
  Tuan D. Pham · bioRxiv · Jun 10, 2026

  Objective To develop a cross-domain spatial AI framework for identifying conserved tissue-state organisation across trauma, oral disease, and cardiovascular tissue using spatial transcriptomic data. Methods Four public spatial transcriptomi…

• AllDayNav: Lifelong Navigation via Real-World Reinforcement Learning
  Hang Yin, Yinan Liang, Jiazhao Zhang, Jiahang Liu et al. · arXiv · Jun 9, 2026

  Lifelong embodied navigation in dynamic environments requires robots to form persistent scene understanding from fragmentary observations, which remains difficult for existing methods that rely on explicit maps or scene graphs and struggle …

• Meridian: Metric-Semantic Primitive Matching for Cross-View Geo-Localization Beyond Urban Environments
  Mason Peterson, Qingyuan Li, Yixuan Jia, Fernando Cladera et al. · arXiv · Jun 4, 2026

  Successful robot automation requires accurate global localization to support repeatability, task planning, goal specification, and safe operation. However, reliable localization in GNSS-denied environments remains an open problem. Overhead …

• RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning
  Ziyang Yu, Xiang Li, Qiong Chang, Jun Miyazaki · arXiv · Jun 4, 2026

  Point clouds are a primary sensory representation for robotic perception, underpinning LiDAR-based autonomous driving, simultaneous localization and mapping (SLAM), and navigation. Within these pipelines, Farthest Point Sampling (FPS) is th…

• Breaking Time: A Fully Gaussian Framework for Distributed and Continuous-Time SLAM
  Davide Ceriola, Simone Ferrari, Luca Di Giammarino, Leonardo Brizi et al. · arXiv · Jun 4, 2026

  Continuous-time SLAM provides a principled framework for fusing heterogeneous sensors while estimating smooth trajectories, and is particularly well-suited for handling heterogeneous, asynchronous sensor streams with non-uniform readout pat…

• DGSG-Mind: Dynamic 3D Gaussian Scene Graphs for Long-Term Scene Understanding and Grounding
  Luzhou Ge, Xiangyu Zhu, Jinyan Liu, Xuesong Li · arXiv · May 28, 2026

  Integrating open-vocabulary semantic information into dynamic 3D scene representations is essential for long-term embodied scene understanding. However, existing methods often suffer from fragile instance association due to incomplete cross…

• Spatial AI consistently preferred to state-of-the-art hearing aids in multitalker noise.
  Cole Morris, Igor Lovchinsky, Christina Callahan, K. Wallace et al. · International Journal of Audiology · May 11, 2026

  OBJECTIVE We examined the Spatial AI model running on the Fortell AI hearing aids to see whether it improves perceived ease of understanding in noisy, multitalker environments relative to hearing aids using more traditional processing. DE…

• Spatial AI in cancer: mapping immune evasion topology through multi-modal omics and deep learning
  L. Lang, Yu Cui, Haimei Wang, Yan-Hong Xiao · Frontiers in Oncology · Apr 15, 2026

  Immune checkpoint blockade has transformed cancer therapy, achieving lasting responses in some patients, yet most still encounter primary or acquired resistance. Recent evidence demonstrates that this resistance is driven not only by intrin…

• ANALISIS KEBIJAKAN TRANSMIGRASI DI KABUPATEN SORONG MENGGUNAKAN PENDEKATAN SPATIAL-AI
  La Ibal, Abdullah Galib Kilwo · Accounting Student Series on Emerging Trends · Mar 31, 2026

  This research examines the transmigration policy in Sorong Regency, Southwest Papua Province, using the QGIS Processing-based SPATIALIS-AI (Spatial Intelligence for Policy and Objective Synthesis) approach. The main objective of the study i…

• From Perception to Action: Spatial AI Agents and World Models
  Gloria Felicia, Nolan Bryant, Handi Putra, Ayaan Gazali et al. · arXiv.org · Feb 2, 2026

  While large language models have become the prevailing approach for agentic reasoning and planning, their success in symbolic domains does not readily translate to the physical world. Spatial intelligence, the ability to perceive 3D structu…

• Non-spatial AI modeling to estimate traffic volume measures on local roadways
  M. Mimi, Subasish Das, Anandi K. Dutta · International Journal of Urban Sciences · Jan 7, 2026