犬には障害物でなく人間には危険：盲導犬ロボットのための共自我ナビゲーションシステム
Not an Obstacle for Dog, but a Hazard for Human: A Co-Ego Navigation System for Guide Dog Robots
盲導犬ロボットのナビゲーションにおいて、ロボットの地面センサーでは検知できないが人間の身長では危険な障害物（例：曲がった枝）を扱うため、ユーザーの視点を統合した二重分岐の回避システムを提案し、実験で有効性を示した。
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著者: Ruiping Liu, Jingqi Zhang, Junwei Zheng, Yufan Chen, Peter Seungjune Lee, Di Wen, Kunyu Peng, Jiaming Zhang, Kailun Yang, Katja Mombaur, Rainer Stiefelhagen
分類: cs.RO
原文アブストラクト
Guide dogs offer independence to Blind and Low-Vision (BLV) individuals, yet their limited availability leaves the vast majority of BLV users without access. Quadruped robotic guide dogs present a promising alternative, but existing systems rely solely on the robot's ground-level sensors for navigation, overlooking a critical class of hazards: obstacles that are transparent to the robot yet dangerous at human body height, such as bent branches. We term this the viewpoint asymmetry problem and present the first system to explicitly address it. Our Co-Ego system adopts a dual-branch obstacle avoidance framework that integrates the robot-centric ground sensing with the user's elevated egocentric perspective to ensure comprehensive navigation safety. Deployed on a quadruped robot, the system is evaluated in a controlled user study with sighted participants under blindfold across three conditions: unassisted, single-view, and cross-view fusion. Results demonstrate that cross-view fusion significantly reduces collision times and cognitive load, verifying the necessity of viewpoint complementarity for safe robotic guide dog navigation.
