Transforming a Quadruped into a Guide Robot for the Visually Impaired:
Formalizing Wayfinding, Interaction Modeling, and Safety Mechanism
- URL: http://arxiv.org/abs/2306.14055v1
- Date: Sat, 24 Jun 2023 20:47:36 GMT
- Title: Transforming a Quadruped into a Guide Robot for the Visually Impaired:
Formalizing Wayfinding, Interaction Modeling, and Safety Mechanism
- Abstract summary: A guide robot has great potential to resolve the limited availability of guide animals that are accessible to only two to three percent of the potential blind or visually impaired (BVI) users.
This paper explores three key topics: (1) formalizing the navigation mechanism of a guide dog and a human, (2) developing a data-driven model of their interaction, and (3) improving user safety.
- Score: 20.767170577136326
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: This paper explores the principles for transforming a quadrupedal robot into
a guide robot for individuals with visual impairments. A guide robot has great
potential to resolve the limited availability of guide animals that are
accessible to only two to three percent of the potential blind or visually
impaired (BVI) users. To build a successful guide robot, our paper explores
three key topics: (1) formalizing the navigation mechanism of a guide dog and a
human, (2) developing a data-driven model of their interaction, and (3)
improving user safety. First, we formalize the wayfinding task of the
human-guide robot team using Markov Decision Processes based on the literature
and interviews. Then we collect real human-robot interaction data from three
visually impaired and six sighted people and develop an interaction model
called the ``Delayed Harness'' to effectively simulate the navigation behaviors
of the team. Additionally, we introduce an action shielding mechanism to
enhance user safety by predicting and filtering out dangerous actions. We
evaluate the developed interaction model and the safety mechanism in
simulation, which greatly reduce the prediction errors and the number of
collisions, respectively. We also demonstrate the integrated system on a
quadrupedal robot with a rigid harness, by guiding users over $100+$~m
trajectories.
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