DogSurf: Quadruped Robot Capable of GRU-based Surface Recognition for Blind Person Navigation
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Abstract (arXiv)
This paper introduces DogSurf - a newapproach of using quadruped robots to help visually impaired people navigate in real world. The presented method allows the quadruped robot to detect slippery surfaces, and to use audio and haptic feedback to inform the user when to stop. A state-of-the-art GRU-based neural network architecture with mean accuracy of 99.925% was proposed for the task of multiclass surface classification for quadruped robots. A dataset was collected on a Unitree Go1 Edu robot. The dataset and code have been posted to the public domain.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 18 references that are in the map. First posted on arXiv 5 Feb 2024.
Builds on
8 of 18 references.
References · 8
- 2017Attention Is All You Needcited by 59,932
- 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,341
- 2021Robotic Guide Dog: Leading a Human with Leash-Guided Hybrid Physical Interactioncited by 14
- 2022Quadruped Guidance Robot for the Visually Impaired: A Comfort-Based Approachcited by 7
- 2022System Configuration and Navigation of a Guide Dog Robot: Toward Animal Guide Dog-Level Guiding Workcited by 6
- 2019Surface Type Classification for Autonomous Robot Indoor Navigationcited by 4
- 2022DogTouch: CNN-based Recognition of Surface Textures by Quadruped Robot with High Density Tactile Sensorscited by 3
- 2023Terrain Recognition and Contact Force Estimation through a Sensorized Paw for Legged Robotscited by 2
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Citing papers per year: 2026: 1.
1 paper.