arXiv AI
Jun 8
SCOUT: Semantic scene COverage via Uncertainty-guided Traversal
arXiv:2606. 06721v1 Announce Type: cross Abstract: Robots that operate over extended periods should not merely visit space; they should progressively understand it.
Beyond Frontiers: Scene-Anomaly Guided Autonomous Exploration
Autonomous exploration of unknown 3D environments is traditionally driven by coverage-maximizing geometric heuristics. However, these methods typically determine exploration targets without considering the underlying structural context.
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arXiv AI
Sep 1
SGE: Semantically-Guided Exploration for Unstructured Environments via Image-Space Waypoint Sampling
arXiv:2608.29315v1 Announce Type: cross Abstract: This work introduces Semantically-Guided Exploration (SGE), a modular exploration framework for ground vehicles that integrates pixel-level semantic...
arXiv Computer Vision
Sep 11
Diagnosing and Dynamically Filtering Occupancy World Models for Active Mapping
The paper investigates how inaccuracies in pretrained occupancy networks affect active mapping robots that select camera viewpoints to reconstruct unknown 3D scenes. By fixing the planner and varying the occupancy representation—ranging from no completion to ground‑truth occupancy—the authors find that correcting false positives or false negatives alone does not reliably improve coverage, highlighting a disconnect between occupancy accuracy and planning performance. They propose a dynamic filtering strategy that retains predictions in unexplored space while suppressing unsupported occupancy based on online observations, which preliminarily shows it can steer viewpoint selection toward reachable surfaces that would otherwise remain unseen.
Hugging Face Trending Papers
Aug 6
Prior-SG: Task and Prior Driven Region Segmentation for Scene Graphs in Arbitrarily-Structured Environments
Hierarchical 3D scene graphs are a promising representation for high-level spatial reasoning in autonomous mobile platforms. However, existing extraction frameworks typically rely on purely local visual clustering or strict geometric heuristics, such as wall-separated rooms, which fail in open-plan or arbitrarily-structured environments.
arXiv AI
Jun 8
MatterDoor: Sampling Zero-shot Spatio-semantic Priors using Generative Models
arXiv:2510. 11014v2 Announce Type: replace-cross Abstract: Autonomous robots often view rooms only partially, through a doorway, where the walls and scene structure hide the geometry and task-relevant semantics needed for safe navigation and goal-directed action.
arXiv AI
Jun 18
EffiNav: Fusing Depth and Vision-Language for Efficient Object Goal Navigation
arXiv:2606. 18634v1 Announce Type: cross Abstract: To locate a target object while exploring the unknown environment is a fundamental capability for autonomous agents, with applications ranging from search-and-rescue to field robots.
arXiv AI
Jun 15
Schr\"odinger's Navigator: Imagining an Ensemble of Futures for Zero-Shot Object Navigation
arXiv:2512. 21201v3 Announce Type: replace-cross Abstract: Zero-shot object navigation (ZSON) requires robots to find target objects in unseen environments without task-specific fine-tuning or pre-built maps, a key capability for general-purpose service robots.
arXiv AI
Jul 1
MVP-Nav: Multi-layer Value Map Planner Navigator
arXiv:2606. 31919v1 Announce Type: cross Abstract: Zero-shot Object Goal Navigation (ZSON) with RGB-only perception poses a fundamental challenge for embodied agents, as the absence of explicit depth information introduces severe physical uncertainty and semantic-physical misalignment.
Hugging Face Trending Papers
Sep 22
CODA: Depth-Aligned Scene Completion and Object Decomposition from a Single RGB-D Image
Robots operating safely in cluttered everyday environments often need to infer scene geometry from partial observations. Methods that detect objects in 2D and reconstruct them independently struggle i...
arXiv Computer Vision
Sep 23
VEOcc: Voxel-Centric Online Semantic Occupancy Prediction For Embodied Scene Understanding
arXiv:2605.25059v4 Announce Type: replace Abstract: Crucial for autonomous exploration, online 3D occupancy prediction and mapping incrementally construct dense spatial representations on the fly. Em...
Hugging Face Trending Papers
Jun 1
RoboDream: Compositional World Models for Scalable Robot Data Synthesis
Scaling robot learning requires large-scale, diverse demonstrations, yet real-world data collection via teleoperation remains prohibitively expensive and time-consuming. While video diffusion models offer a promising avenue for data scaling, existing generative approaches are often limited to superficial visual augmentation, or suffer from embodiment hallucinations that yield physically infeasible motions.
arXiv AI
Aug 3
AREA3D: Active Reconstruction Agent with Unified Feed-Forward 3D Perception and Vision-Language Guidance
arXiv:2512. 05131v2 Announce Type: replace-cross Abstract: Active 3D reconstruction enables an agent to autonomously select viewpoints to efficiently obtain accurate and complete scene geometry, rather than passively reconstructing scenes from pre-collected images.