A Demo of DIAM: Drone-based Indoor Accessibility Mapping

Indoor mapping data is crucial for navigation and accessibility, yet such data are widely lacking due to the manual labor and expense of data collection, especially for larger indoor spaces. In this demo paper, we introduce Drone-based Indoor Accessibility Mapping (DIAM), a drone-based indoor scanning system that efficiently produces 3D reconstructions of indoor spaces with automatically recognized and located accessibility features/barriers such as stairs, elevators, and doors automatically. With DIAM, our goal is to 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.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3672539.3686782
Citations
6
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
7.79
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A Demo of DIAM: Drone-based Indoor Accessibility Mapping

Jon E. Froehlich, Xia Su, Ruiqi Chen, Weiye Zhang et al.
6 citations
Robotics and Sensor-Based Localization
7.79
article

A Demo of DIAM: Drone-based Indoor Accessibility Mapping

Jon E. Froehlich, Xia Su, Ruiqi Chen, Weiye Zhang, Jingwei Ma
article en
6 citations

Abstract

Indoor mapping data is crucial for navigation and accessibility, yet such data are widely lacking due to the manual labor and expense of data collection, especially for larger indoor spaces. In this demo paper, we introduce Drone-based Indoor Accessibility Mapping (DIAM), a drone-based indoor scanning system that efficiently produces 3D reconstructions of indoor spaces with automatically recognized and located accessibility features/barriers such as stairs, elevators, and doors automatically. With DIAM, our goal is to 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.

University of Washington (US)
Openalex Percentile: Top 3%
Robotics and Sensor-Based Localization
7.79
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