[Massachusetts-NFB] FW: [NFBV-Announce] Research Participation Request: INVLM-Based Indoor Navigation System for People with Visual Impairments

Fri Oct 17 16:23:50 UTC 2025

Shara Winton

President, National federation of the Blind of Massachusetts

 <http://www.nfbma.org/> www.nfbma.org

 <mailto:sharawinton at gmail.com> sharawinton at gmail.com

617-304-0347

From: NFBV-Announce <nfbv-announce-bounces at nfbnet.org> On Behalf Of David
Andrews via NFBV-Announce
Sent: Thursday, October 16, 2025 12:52 AM
To: david.andrews at nfbnet.org
Subject: [NFBV-Announce] Research Participation Request: INVLM-Based Indoor
Navigation System for People with Visual Impairments

Research Participation Request: INVLM-Based Indoor Navigation System for
People with Visual Impairments

The below research participant solicitation is being provided for
informational purposes only. The National Federation of the Blind has no
involvement in this research, but we believe that it may contribute to our
research mission.

Research Title:  InVLM: VLM-Based Indoor Navigation System for People with
Visual Impairments

Being conducted by: University of Maryland, Baltimore County

Purpose of the Study

This study aims to develop and evaluate an indoor navigation system known as
InVLM (Vision-Language Model-based Indoor Navigation System) for individuals
with visual impairments. This system integrates Multi-Modal Foundation
Models with real-time object detection and spatial awareness technologies to
enhance effective navigation in dynamic indoor settings. The study aims to
evaluate the system's effects on navigation efficiency, user independence,
and safety compared to traditional assistive methods.  In this research, we
propose a novel navigation assistance system that integrates macro and
micro-navigation for goal-based navigation with the power of multi-modal
foundation models. This system can assist BLV individuals in navigating
dynamic indoor areas. To ensure safe navigation, we integrate a real-time
open-world object detection model, YOLO-World, as an auxiliary model
alongside a Large Language Model (LLM) for more robust obstacle detection
and hazard assessment. To provide macro navigation, our system uses
LLM-based floor plan analysis to convert layouts into navigable graph
representations while generating contextual rules and trajectories. Our
system combines high-level route generation with low-level navigation to
provide more efficient and precise guidance in different indoor areas. To
increase rerouting capabilities for user reorientation, we integrate
image-based localization through image feature matching with the help of
Vision Language Models (VLMs) to detect each scene in an indoor area.
Although comprehensive experimental results are still pending, preliminary
trials demonstrate significant improvements in navigation efficiency and
user independence.

Role of the Participants and Anticipated Length of the Study 

Eligibility Criteria 

We are looking for participants who 

*	are blind or have low vision,  
*	Currently working in creative domains or have experience with
creative tasks. Creative domains may include different forms of art such as
photography, creative writing (e.g., fictions), drawing, fiber arts, music,
etc. or professions that include creating prototypes or design materials,
such as interaction design, product design, graphics design, user experience
(UI/UX) research and design, etc.  
*	are able to communicate in English,  
*	are 18 years old or above  

By creative artifacts, we refer to design prototypes, tactile arts and
crafts, images, photographs, drawings, creative writing samples (e.g.,
fiction, but not academic papers at this time), and musical compositions.
These artifacts can be in any medium, as long as they were created by the
participant as part of their creative practice.

Activities: Short questionnaire, brief training, and navigation tasks with a
sighted assistant

Each participant will be asked to complete a set of 5 to 10 navigation tasks
selected from the following list. These tasks are designed to evaluate
wayfinding, navigation, and obstacle detection. A description of each task
is provided below.

1. Point-to-Point Navigation

A.  Example for this Task: Move from the entrance of the space to a
designated room (e.g., bedroom, conference room).

 Goal: Evaluate the systems ability to guide users through multiple turns or
corridors.

we will evaluate different functionalities of our system, including scene
descriptions, text to speech efficiency to the user

Obstacle Avoidance

Task: Follow a path that includes one or more obstacles (e.g., chairs,
boxes) and avoid them based on verbal guidance. Goal: Evaluate the systems
hazard detection and redirection capabilities.

Safety: No face camera; safety support provided

Proposed Participant Compensation

Yes, . Compensation:

o   Pre-survey: $15 (10 -15 minutes, BLV participants only) 

https://forms.gle/REBMwfqQf76xSrVE8 

You can now fill out the pre-survey, which will take approximately 10-15
minutes to complete (BLV participants only).

In-person sessions: $40 per session (30 - 45 minutes, up to 3 sessions in
one day)

Link or Instructions for Participants to Enter the Study 

Sign-up form: https://umbc.co1.qualtrics.com/jfe/form/SV_eyUrWciWyZjEg62 

Consent form :
https://drive.google.com/file/d/13K0RjJFEL8sZfJ2wHllpQCA6d0aI3BYd/view?usp=s
haring 

Contact the following individual with any questions 

Aydin Ayanzadeh

3013102304

aydina1 at umbc.edu <mailto:aydina1 at umbc.edu> 

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