A Sparse Topometric Graph for Scalable Cross-Session Indoor Navigation
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
The Flow has not summarised this story yet — read it at arXiv Computer Vision.
Building memory is essential for long-horizon planning in zero-shot embodied navigation. Detector-centric scene graphs often compress observations into sparse nodes, discarding fine-grained visual evidence and accumulating noise, while 3D reconstruction-based methods remain computationally prohibitive.
arXiv:2606.16569v2 Announce Type: replace Abstract: Registering two captures of the same indoor space taken at different times underpins persistent spatial memory for robots and AR systems, yet the r...
SceneTeract is a verification interface that separates semantic action understanding from physical feasibility in indoor 3D scenes. It decomposes activities into atomic actions and performs explicit geometric checks to determine executability, providing diagnostic traces for failures. The system reveals widespread functional and accessibility issues in synthetic scenes, shows that existing VLMs over‑predict action feasibility, and improves VLM performance through post‑training with verifier feedback, with benefits that generalize to real‑world scenes.
Reading the Room (RR) is a global‑local method that registers scale‑ambiguous, sparse semantic VSLAM maps to partially built floor plans. It introduces a single robust, differentiable, class‑balanced semantic‑geometric energy function that drives all pipeline stages, and offers two global initialization schemes—one using a single user‑provided correspondence and another using a cross‑modal matching network. Evaluated on 33 sequences from three construction sites, RR outperforms classical and learning‑based baselines, improving mean absolute trajectory error by 4.5× overall and 7.6× when an anchor is supplied.
arXiv:2607. 14514v1 Announce Type: cross Abstract: Object-goal navigation requires an embodied agent to locate and reach an instance of a specified object category in an indoor environment.
arXiv:2609.38620v1 Announce Type: new Abstract: Neural implicit representations have had a significant impact on scene reconstruction by enabling robots to build continuous, differentiable, and high-...