2409627
Cooperative Agreement
Overview
Grant Description
SBIR Phase II: A handheld fine-grained radio frequency identification (RFID) localization system for retail automation.
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to help U.S. retailers and consumers save billions of dollars, while enhancing the technological competitiveness and sustainability of the United States of America.
Specifically, this project will improve labor efficiency for retailers, thus alleviating the $27B labor shortage they face today.
By cutting labor costs, the product would not only help retailers but also tame retail inflation to end-consumers.
Furthermore, by introducing cost-effective solutions to brick-and-mortar retailers, this project will boost their competitiveness with e-commerce giants, resulting in better quality and prices and higher customer satisfaction.
The developed technology will also help supply chain operations become more sustainable by enabling industries to reduce excess inventory, improve end-of-life item returns, and repurpose old goods.
Finally, the project will bring a new generation of indoor positioning technologies to the retail and supply chain sectors, elevating the experience for retail workers and shoppers.
This Small Business Innovation Research (SBIR) Phase I project seeks to design, build, and evaluate a system for inventory tracking in retail stores by leveraging mobile radio frequency (RF) identification (RFID) technology.
The proposed plan has multiple technical objectives: (1) developing computer vision machine learning models for automatic map creation and updates, (2) designing algorithms for robust self-localization of the handheld mobile device indoors, (3) developing RF-visual sensor fusion algorithms for item-level 3D localization, and (4) developing augmented reality-based user interfaces for scanning and navigating indoor environments.
The technical contributions will go beyond designing the algorithms to implementing them on a mobile-to-cloud platform and evaluating them in real retail stores.
This project will advance the state-of-the-art in indoor positioning and mapping, impacting the fields of mobile vision, RF localization, split computing, and human-computer interaction.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.
Subawards are not planned for this award.
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to help U.S. retailers and consumers save billions of dollars, while enhancing the technological competitiveness and sustainability of the United States of America.
Specifically, this project will improve labor efficiency for retailers, thus alleviating the $27B labor shortage they face today.
By cutting labor costs, the product would not only help retailers but also tame retail inflation to end-consumers.
Furthermore, by introducing cost-effective solutions to brick-and-mortar retailers, this project will boost their competitiveness with e-commerce giants, resulting in better quality and prices and higher customer satisfaction.
The developed technology will also help supply chain operations become more sustainable by enabling industries to reduce excess inventory, improve end-of-life item returns, and repurpose old goods.
Finally, the project will bring a new generation of indoor positioning technologies to the retail and supply chain sectors, elevating the experience for retail workers and shoppers.
This Small Business Innovation Research (SBIR) Phase I project seeks to design, build, and evaluate a system for inventory tracking in retail stores by leveraging mobile radio frequency (RF) identification (RFID) technology.
The proposed plan has multiple technical objectives: (1) developing computer vision machine learning models for automatic map creation and updates, (2) designing algorithms for robust self-localization of the handheld mobile device indoors, (3) developing RF-visual sensor fusion algorithms for item-level 3D localization, and (4) developing augmented reality-based user interfaces for scanning and navigating indoor environments.
The technical contributions will go beyond designing the algorithms to implementing them on a mobile-to-cloud platform and evaluating them in real retail stores.
This project will advance the state-of-the-art in indoor positioning and mapping, impacting the fields of mobile vision, RF localization, split computing, and human-computer interaction.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.
Subawards are not planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH PHASE II (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE II", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23516
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Cambridge,
Massachusetts
02141-1277
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the End Date has been extended from 07/31/26 to 01/31/29 and the total obligations have increased 70% from $1,000,000 to $1,699,528.
Cartesian Systems was awarded
Cooperative Agreement 2409627
worth $1,699,528
from National Science Foundation in August 2024 with work to be completed primarily in Cambridge Massachusetts United States.
The grant
has a duration of 4 years 5 months and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Cooperative Agreement was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase II Programs (SBIR/STTR Phase II).
SBIR Details
Research Type
SBIR Phase II
Title
SBIR Phase II: A Handheld Fine-Grained Radio Frequency IDentification (RFID) Localization System for Retail Automation
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to help US retailers and consumers save billions of dollars, while enhancing the technological competitiveness and sustainability of the United States of America. Specifically, this project will improve labor efficiency for retailers, thus alleviating the $27B labor shortage they face today. By cutting labor costs, the product would not only help retailers but also tame retail inflation to end-consumers. Furthermore, by introducing cost-effective solutions to brick-and-mortar retailers, this project will boost their competitiveness with e-commerce giants, resulting in better quality and prices and higher customer satisfaction. The developed technology will also help supply chain operations become more sustainable by enabling industries to reduce excess inventory, improve end-of-life item returns, and repurpose old goods. Finally, the project will bring a new generation of indoor positioning technologies to the retail and supply chain sectors, elevating the experience for retail workers and shoppers.
This Small Business Innovation Research (SBIR) Phase I project seeks to design, build, and evaluate a system for inventory tracking in retail stores by leveraging mobile radio frequency (RF) identification (RFID) technology. The proposed plan has multiple technical objectives: (1) developing computer vision machine learning models for automatic map creation and updates, (2) designing algorithms for robust self-localization of the handheld mobile device indoors, (3) developing RF-visual sensor fusion algorithms for item-level 3D localization, and (4) developing augmented reality-based user interfaces for scanning and navigating indoor environments. The technical contributions will go beyond designing the algorithms to implementing them on a mobile-to-cloud platform and evaluating them in real retail stores. This project will advance the state-of-the-art in indoor positioning and mapping, impacting the fields of mobile vision, RF localization, split computing, and human computer interaction.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Topic Code
W
Solicitation Number
NSF 23-516
Status
(Ongoing)
Last Modified 9/18/25
Period of Performance
8/15/24
Start Date
1/31/29
End Date
Funding Split
$1.7M
Federal Obligation
$0.0
Non-Federal Obligation
$1.7M
Total Obligated
Activity Timeline
Transaction History
Modifications to 2409627
Additional Detail
Award ID FAIN
2409627
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
LE2UZ9EC2KQ4
Awardee CAGE
99Q65
Performance District
MA-07
Senators
Edward Markey
Elizabeth Warren
Elizabeth Warren
Modified: 9/18/25