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Main Authors: Liu, Ruiping, Zhang, Jingqi, Zheng, Junwei, Chen, Yufan, Lee, Peter Seungjune, Wen, Di, Peng, Kunyu, Zhang, Jiaming, Yang, Kailun, Mombaur, Katja, Stiefelhagen, Rainer
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2603.20121
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author Liu, Ruiping
Zhang, Jingqi
Zheng, Junwei
Chen, Yufan
Lee, Peter Seungjune
Wen, Di
Peng, Kunyu
Zhang, Jiaming
Yang, Kailun
Mombaur, Katja
Stiefelhagen, Rainer
author_facet Liu, Ruiping
Zhang, Jingqi
Zheng, Junwei
Chen, Yufan
Lee, Peter Seungjune
Wen, Di
Peng, Kunyu
Zhang, Jiaming
Yang, Kailun
Mombaur, Katja
Stiefelhagen, Rainer
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2603_20121
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Not an Obstacle for Dog, but a Hazard for Human: A Co-Ego Navigation System for Guide Dog Robots
Liu, Ruiping
Zhang, Jingqi
Zheng, Junwei
Chen, Yufan
Lee, Peter Seungjune
Wen, Di
Peng, Kunyu
Zhang, Jiaming
Yang, Kailun
Mombaur, Katja
Stiefelhagen, Rainer
Robotics
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.
title Not an Obstacle for Dog, but a Hazard for Human: A Co-Ego Navigation System for Guide Dog Robots
topic Robotics
url https://arxiv.org/abs/2603.20121