RASSAR

Quick Info

Project Date May 1, 2022 - Present
PIs: Jon E. Froehlich (PI)
Keywords: mixed-reality, accessibility, computer vision, mobile phone, AI for accessibility

News

Daniel Presents on Behalf of the Makeability Lab at Ability/LEAP Accessibility Research Night

Nov 17, 2022 | Xia

Daniel presents the recent work of the Makeability Lab at the Ability/LEAP Accessibility Research Night. Congrats to the successful talk! Here's a copy of the presentation.

Xia Presents RASSAR at CSE Industry Affiliates Research Day Session Hosted by Jon

Nov 15, 2022 | Xia

Xia Su presented his recent work on the RASSAR project at the annual CSE Industry Affiliates Research Day. Interestingly, the session of the presentation is hosted by Jon! Such a nice collab between the wonderful Makability Lab members! Congrats to the team!

About

RASSAR Detection Results

RASSAR could scan and detect access/safety issues in indoor spaces. This figure shows the 2 types of issue: object dimension issue (left) and dangerous item issue (right))

To help improve the safety and accessibility of indoor spaces, researchers and health professionals have created assessment instruments that enable homeowners and trained experts to audit and improve homes. With advances in computer vision, augmented reality (AR), and mobile sensors, new approaches are now possible. We introduce RASSAR (Room Accessibility and Safety Scanning in Augmented Reality), a new proof-of-concept prototype for semi-automatically identifying, categorizing, and localizing indoor accessibility and safety issues using LiDAR + camera data, machine learning, and AR. We present an overview of the current RASSAR prototype and a preliminary evaluation in a single home.