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2208902

Project Grant

Overview

Grant Description
Sttr Phase I: Integrating Vision-Guided Collaborative Robots for Postharvest Processing of Produce - The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to empower the processors of harvested fruits and vegetables with the flexibility to use robotic automation to meet their labor needs. The automation uses collaborative robots (COBOTS) guided by computer vision, which are potentially safe around humans. The technology will help assure consistent produce quality and processing rates.

Through a robust COBOT-based solution, the project will provide an affordable, sustainable, and safe means for farms of all sizes to keep up with their production goals, which will sustain competition and the nation's food supply. This project has the added benefit of upskilling workers in farms by creating openings for more technically oriented positions, both in monitoring and maintaining the COBOTS.

Instead of tediously programming the COBOT for each use, the project is introducing a new way of translating the tasks performed by humans to the COBOT by learning from camera recordings. It will also improve understanding of how COBOTS can safely be used alongside humans in a shared working space.

This Small Business Technology Transfer (STTR) Phase 1 project aims to make it possible to use COBOTS with human workers on tasks that go beyond the traditional pick-and-place. The proposed technology will automate processing line tasks that require computer vision, which is challenging because accurate and reliable perception must guide the robot's motion.

Research has coalesced the technical challenges on the path to a viable commercial product around five steps. These start with a formal description of the task domain followed by using robust implementations of noise-tolerant machine learning algorithms for automatically learning the task, and end with a solution that integrates the learned task behavior with a vision-guided COBOT system.

Phase 1 will support research toward addressing two problems. The first is to design an intuitive way to elicit a precise specification of the client's task domain. A digital conversational assistant will utilize multiple modalities for the elicitation. The second is the inability of available implementations to generate coworker-aware and efficient COBOT movements. The research will investigate and develop significant improvements to the COBOT motion to improve coworker safety while reducing the processing time by an expected 50%.

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.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM PHASE I", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF21563
Place of Performance
Athens, Georgia 30602-0001 United States
Geographic Scope
Single Zip Code
Related Opportunity
21-563
Analysis Notes
Amendment Since initial award the End Date has been extended from 09/30/23 to 12/31/24.
Inversai was awarded Project Grant 2208902 worth $212,153 from in January 2023 with work to be completed primarily in Athens Georgia United States. The grant has a duration of 2 years and was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.

SBIR Details

Research Type
STTR Phase I
Title
STTR Phase I:Integrating Vision-Guided Collaborative Robots for Postharvest Processing of Produce
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to empower the processors of harvested fruits and vegetables with the flexibility to use robotic automation to meet their labor needs. The automation uses collaborative robots (cobots) guided by computer vision, which are potentially safe around humans. The technology will help assure consistent produce quality and processing rates. Through a robust cobot-based solution, the project will provide an affordable, sustainable, and safe means for farms of all sizes to keep up with their production goals, which will sustain competition and the nation’s food supply. This project has the added benefit of upskilling workers in farms by creating openings for more technically oriented positions, both in monitoring and maintaining the cobots. Instead of tediously programming the cobot for each use, the project is introducing a new way of translating the tasks performed by humans to the cobot by learning from camera recordings. It will also improve understanding of how cobots can safely be used alongside humans in a shared working space._x000D_ _x000D_ This Small Business Technology Transfer (STTR) Phase 1 project aims to make it possible to use cobots with human workers on tasks that go beyond the traditional pick-and-place. The proposed technology will automate processing line tasks that require computer vision, which is challenging because accurate and reliable perception must guide the robot’s motion. Research has coalesced the technical challenges on the path to a viable commercial product around five steps. These start with a formal description of the task domain followed by using robust implementations of noise-tolerant machine learning algorithms for automatically learning the task, and end with a solution that integrates the learned task behavior with a vision-guided cobot system. Phase 1 will support research toward addressing two problems. The first is to design an intuitive way to elicit a precise specification of the client’s task domain. A digital conversational assistant will utilize multiple modalities for the elicitation. The second is the inability of available implementations to generate coworker-aware and efficient cobot movements. The research will investigate and develop significant improvements to the cobot motion to improve coworker safety while reducing the processing time by an expected 50%._x000D_ _x000D_ 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
AI
Solicitation Number
NSF 21-563

Status
(Complete)

Last Modified 7/8/24

Period of Performance
1/15/23
Start Date
12/31/24
End Date
100% Complete

Funding Split
$212.2K
Federal Obligation
$0.0
Non-Federal Obligation
$212.2K
Total Obligated
100.0% Federal Funding
0.0% Non-Federal Funding

Activity Timeline

Interactive chart of timeline of amendments to 2208902

Transaction History

Modifications to 2208902

Additional Detail

Award ID FAIN
2208902
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
QENNBEH1KM63
Awardee CAGE
None
Performance District
GA-10
Senators
Jon Ossoff
Raphael Warnock

Budget Funding

Federal Account Budget Subfunction Object Class Total Percentage
Research and Related Activities, National Science Foundation (049-0100) General science and basic research Grants, subsidies, and contributions (41.0) $212,153 100%
Modified: 7/8/24