mlsanityData to 7 Oct 2026

Active Neural Mapping at Scale

arXiv 2409.20276 ↗First posted 30 Sep 2024cs.CV cs.ROcited by 8

Not on the map. Why?

Abstract (arXiv)

We introduce a NeRF-based active mapping system that enables efficient and robust exploration of large-scale indoor environments. The key to our approach is the extraction of a generalized Voronoi graph (GVG) from the continually updated neural map, leading to the synergistic integration of scene geometry, appearance, topology, and uncertainty. Anchoring uncertain areas induced by the neural map to the vertices of GVG allows the exploration to undergo adaptive granularity along a safe path that traverses unknown areas efficiently. Harnessing a modern hybrid NeRF representation, the proposed system achieves competitive results in terms of reconstruction accuracy, coverage completeness, and exploration efficiency even when scaling up to large indoor environments. Extensive results at different scales validate the efficacy of the proposed system.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 32 of its 45 references that are in the map. First posted on arXiv 30 Sep 2024.

Builds on

32 of 45 references.

References · 32

  1. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
  2. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,214
  3. 2017Matterport3D: Learning from RGB-D Data in Indoor Environmentscited by 1,354
  4. 2019Habitat: A Platform for Embodied AI Researchcited by 1,163
  5. 2023Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fieldscited by 667
  6. 2021NICE-SLAM: Neural Implicit Scalable Encoding for SLAMcited by 586
  7. 2023LERF: Language Embedded Radiance Fieldscited by 538
  8. 2018Gibson Env: Real-World Perception for Embodied Agentscited by 477
  9. 2021iMAP: Implicit Mapping and Positioning in Real-Timecited by 476
  10. 2021In-Place Scene Labelling and Understanding with Implicit Scene Representationcited by 411
  11. 2020Learning to Explore using Active Neural SLAMcited by 308
  12. 2023NoMaD: Goal Masked Diffusion Policies for Navigation and Explorationcited by 234
20 more
  1. 2023Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAMcited by 183
  2. 2023Point-SLAM: Dense Neural Point Cloud-based SLAMcited by 160
  3. 2018Neural Importance Samplingcited by 154
  4. 2021BACON: Band-limited Coordinate Networks for Multiscale Scene Representationcited by 142
  5. 2023GO-SLAM: Global Optimization for Consistent 3D Instant Reconstructioncited by 132
  6. 2022ActiveNeRF: Learning where to See with Uncertainty Estimationcited by 124
  7. 2019Learning Exploration Policies for Navigationcited by 113
  8. 2020Occupancy Anticipation for Efficient Exploration and Navigationcited by 104
  9. 2022Navigating to Objects in the Real Worldcited by 104
  10. 2021A Structured Dictionary Perspective on Implicit Neural Representationscited by 100
  11. 2023Bayes' Rays: Uncertainty Quantification for Neural Radiance Fieldscited by 90
  12. 2022NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representationscited by 54
  13. 2020FUEL: Fast UAV Exploration using Incremental Frontier Structure and Hierarchical Planningcited by 42
  14. 2019An Efficient Sampling-based Method for Online Informative Path Planning in Unknown Environmentscited by 38
  15. 2022Uncertainty-driven Planner for Exploration and Navigationcited by 31
  16. 2021Continual Neural Mapping: Learning An Implicit Scene Representation from Sequential Observationscited by 30
  17. 2023Active Neural Mappingcited by 30
  18. 2024NARUTO: Neural Active Reconstruction from Uncertain Target Observationscited by 27
  19. 2021A Shadowcasting-Based Next-Best-View Planner for Autonomous 3D Explorationcited by 9
  20. 2022Multi-Robot Active Mapping via Neural Bipartite Graph Matchingcited by 8

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 2; 2026: 3.

8 papers.