Project Description

Date

2024–Present

PI

Student Lead

Indoor mapping data is crucial for navigation and accessibility, yet such data are widely lacking due to the high manual labor of data collection, especially for larger indoor spaces. We introduce Drone-based Indoor Accessibility Mapping (DIAM), a drone-based indoor scanning system that efficiently produces 3D reconstructions of indoor spaces with key accessibility facilities recognized and located in the model. With DIAM, users can scan indoor spaces quickly and generate a precise, detailed, and visual 3D indoor accessibility map. We describe DIAM’s system design, present its technical capabilities, and discuss future use cases.

Funding

Publications

A Demo of DIAM: Drone-based Indoor Accessibility Mapping

Xia Su, Ruiqi Chen, Richard Weiye Zhang, Jingwei Ma, Jon E. Froehlich

Extended Abstract UIST 2024 To Appear

PDF | doi | Citation | DIAM: Drone-based Indoor Accessibility Mapping

Talks
AI-Powered AR Accessibility

Aug. 8, 2024 | Apple's HCML Workshop

Cupertino, CA

PDF | PPTX | CookAR | DIAM: Drone-based Indoor Accessibility Mapping | RASSAR | ARTennis | GazePointAR

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We design, build, and evaluate new interactive tools and techniques to address pressing societal challenges. Makeability refers both to how our technological innovations make new abilities possible for humans as well as our educational mission to help students gain new abilities as they learn and grow through research, invention, and human-centered design.

Recent News

Aug. 09, 2024

"AI-Powered AR Accessibility" Talk at Apple Research

June 25, 2024

Chu Li Gives Invited Talk at NYU VIDA

June 24, 2024

Xia and Daniel off to Adobe for the Summer

Links