Automated mapping of accessibility for indoor urban spaces
We consider the use of embedded deep-learning platforms, coupled with mobile robots, to build an automated obstacle identification and mapping solution for mobility-impaired users. Mobile robots, such as UAVs and UGVs, can carry embedded platforms and explore urban structures in search of mobility obstacles to humans, in particular those with disabilities. The end users can include people with disabilities, policy makers, safety inspectors and others concerned with making our environment better navigable by everyone.
The AMAIUS project is being developed at the University of Guanajuato by members of the Vision, Robotics and Artificial Intelligence
Laboratory (LaViRIA). Our team includes the following people:
- Dr. Juan-Pablo Ramirez-Paredes, project lead.
- Dr. Fernando Correa-Tome, machine learning specialist.
- Marco Contreras-Cruz, machine learning specialist.
- J. Abel Vilchis-Mar, machine learning trainee.
- Victor Ayala-Alfaro, roboticist.
This project is sponsored by an AI for Accessibility grant from Microsoft. This initiative provides research laboratories with Azure computing credits to develop solutions to accessibility challenges.