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Touvigation: Embodied Adaptive Object Acquisition for Blind and Low-Vision Users in Unfamiliar Indoor Environments

Paper recorded by Signals 4 on 2026-09-18 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-18 on arXiv · recorded by Signals 4 on 2026-09-21

Category: cs.AI · 人工智能 · first seen 2026-09-21

Abstract

Blind and low-vision users often face challenges when locating and physically acquiring objects in unfamiliar indoor environments. Existing vision-language-model-based assistants can provide semantic descriptions but may introduce latency, hallucinations, and guidance that is poorly aligned with embodied action. We present Touvigation, a hands-free object acquisition system that combines vision-la

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#20 most recent of 320 cs.AI papers we have recorded · ↑ newer: Federated Deep Clustering Networks for High-Dimensional and Heterogene · ↓ older: Coding Agents with an Obstacle-Aware Harness for Safe Robot Manipulati
Cite this page: Touvigation: Embodied Adaptive Object Acquisition for Blind and Low-Vision Users in Unfamiliar Indoor Environments: the #20 most recent of 320 cs.AI papers we have recorded (as of 2026-09-18). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/touvigation-embodied-adaptive-object-acquisition-for-blind-and-low-vision-users-.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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