Robot Patrol: Using Crowdsourcing and Robotic Systems to Provide Indoor
Navigation Guidance to The Visually Impaired
- URL: http://arxiv.org/abs/2306.02843v1
- Date: Mon, 5 Jun 2023 12:49:52 GMT
- Title: Robot Patrol: Using Crowdsourcing and Robotic Systems to Provide Indoor
Navigation Guidance to The Visually Impaired
- Authors: Ike Obi, Ruiqi Wang, Prakash Shukla, Byung-Cheol Min
- Abstract summary: We develop an integrated system that employs a combination of crowdsourcing, computer vision, and robotic frameworks to provide contextual information to the visually impaired.
The system is designed to provide information to the visually impaired about 1) potential obstacles on the route to their indoor destination, 2) information about indoor events on their route which they may wish to avoid or attend, and 3) any other contextual information that might support them to navigate to their indoor destinations safely and effectively.
- Score: 5.973995274784383
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Indoor navigation is a challenging activity for persons with disabilities,
particularly, for those with low vision and visual impairment. Researchers have
explored numerous solutions to resolve these challenges; however, several
issues remain unsolved, particularly around providing dynamic and contextual
information about potential obstacles in indoor environments. In this paper, we
developed Robot Patrol, an integrated system that employs a combination of
crowdsourcing, computer vision, and robotic frameworks to provide contextual
information to the visually impaired to empower them to navigate indoor spaces
safely. In particular, the system is designed to provide information to the
visually impaired about 1) potential obstacles on the route to their indoor
destination, 2) information about indoor events on their route which they may
wish to avoid or attend, and 3) any other contextual information that might
support them to navigate to their indoor destinations safely and effectively.
Findings from the Wizard of Oz experiment of our demo system provide insights
into the benefits and limitations of the system. We provide a concise
discussion on the implications of our findings.
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