2242216
Cooperative Agreement
Overview
Grant Description
Sbir Phase II: Epipolar-Plane Imaging for Robot 3D Vision -The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project seeks to improve robotic interactions with the humans.
Currently, robots are involved in large sectors of society including logistics, manufacturing, autonomous navigation, video communication, remote supervision of complex mechanical maintenance/repair tasks, support in battlefields and disasters, and interactions in various training, educational, and interventional scenarios including telemedicine.
This technology may offer more effective automation in the workplace through higher quality 3D sensing, greater precision visualization, and increased worker quality of life.
The technology addresses precision and reliability of passive 3D scene measurements.
This Small Business Innovation Research (SBIR) Phase II project addresses the acquisition of reliable and precise three-dimensional representations of a scene from passively acquired image data for use in navigation, grasping, manipulation, and other operations of autonomous systems in unrestricted three-dimensional spaces.
This technology has been a long-standing challenge in the computer vision field, with many efforts providing adequate solutions under certain conditions, but lacking applicability across a breadth of applications.
Other approaches typically deliver inaccurate results where there are, for example, repeated structures in the view, thin features, a large range in depth, or where structures align with aspects of the capture geometry.
Based on the matching of features across images, current technologies fail when features have similar appearance.
This technology removes the uncertainty of this process through a low-cost use of over-sampling, using a specific set of additional perspectives to replace the "matching" with deterministic linear filtering.
Increasing the reliability and precision of 3D scene measurements will open new opportunities for robotic interactions with the world.
Success in this project will advance the underlying light-field technology to broader application areas where human-in-the-loop operations using artificial reality/virtual reality (AR/VR) or mixed reality (such as remote collaboration and distance interaction) depend on accurate and responsive visualization and scene modeling, reducing influences of vestibular and proprioceptive mismatch that can cause disruptive effects such as nausea.
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.
Currently, robots are involved in large sectors of society including logistics, manufacturing, autonomous navigation, video communication, remote supervision of complex mechanical maintenance/repair tasks, support in battlefields and disasters, and interactions in various training, educational, and interventional scenarios including telemedicine.
This technology may offer more effective automation in the workplace through higher quality 3D sensing, greater precision visualization, and increased worker quality of life.
The technology addresses precision and reliability of passive 3D scene measurements.
This Small Business Innovation Research (SBIR) Phase II project addresses the acquisition of reliable and precise three-dimensional representations of a scene from passively acquired image data for use in navigation, grasping, manipulation, and other operations of autonomous systems in unrestricted three-dimensional spaces.
This technology has been a long-standing challenge in the computer vision field, with many efforts providing adequate solutions under certain conditions, but lacking applicability across a breadth of applications.
Other approaches typically deliver inaccurate results where there are, for example, repeated structures in the view, thin features, a large range in depth, or where structures align with aspects of the capture geometry.
Based on the matching of features across images, current technologies fail when features have similar appearance.
This technology removes the uncertainty of this process through a low-cost use of over-sampling, using a specific set of additional perspectives to replace the "matching" with deterministic linear filtering.
Increasing the reliability and precision of 3D scene measurements will open new opportunities for robotic interactions with the world.
Success in this project will advance the underlying light-field technology to broader application areas where human-in-the-loop operations using artificial reality/virtual reality (AR/VR) or mixed reality (such as remote collaboration and distance interaction) depend on accurate and responsive visualization and scene modeling, reducing influences of vestibular and proprioceptive mismatch that can cause disruptive effects such as nausea.
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=NSF22552
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Los Altos,
California
94024-3827
United States
Geographic Scope
Single Zip Code
Related Opportunity
22-552
Analysis Notes
Amendment Since initial award the total obligations have increased 2% from $999,407 to $1,015,407.
Epiimaging was awarded
Cooperative Agreement 2242216
worth $1,015,407
from National Science Foundation in September 2023 with work to be completed primarily in Los Altos California 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
SBIR Phase II
Title
SBIR Phase II: Epipolar-Plane Imaging for Robot 3D Vision
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project seeks to improve robotic interactions with the humans.Currently, robots are involved in large sectors of society including logistics, manufacturing, autonomous navigation, video communication, remote supervision of complex mechanical maintenance/repair tasks, support in battlefields and disasters, and interactions in various training, educational, and interventional scenarios including telemedicine. This technology may offer more effective automation in the workplace through higher quality 3D sensing, greater precision visualization and increased worker quality of life. The technology addresses precision and reliability of passive 3D scene measurements. _x000D_ _x000D_ This Small Business Innovation Research (SBIR) Phase II project addresses the acquisition of reliable and precise three-dimensional representations of a scene from passively acquired image data for use in navigation, grasping, manipulation, and other operations of autonomous systems in unrestricted three-dimensional spaces. This technology has been a long-standing challenge in the computer vision field, with many efforts providing adequate solutions under certain conditions, but lacking applicability across a breadth of applications. Other approaches typically deliver inaccurate results where there are, for example, repeated structures in the view, thin features, a large range in depth, or where structures align with aspects of the capture geometry. Based on the matching of features across images, current technologies fail when features have similar appearance. This technology removes the uncertainty of this process through a low-cost use of over-sampling, using a specific set of additional perspectives to replace the “matching” with deterministic linear filtering. Increasing the reliability and precision of 3D scene measurements will open new opportunities for robotic interactions with the world. Success in this project will advance the underlying light-field technology to broader application areas where human-in-the-loop operations using artificial reality/virtual reality (AR/VR) or mixed reality (such as remote collaboration and distance interaction) depend on accurate and responsive visualization and scene modeling, reducing influences of vestibular and proprioceptive mismatch that can cause disruptive effects such as nausea._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
MO
Solicitation Number
NSF 22-552
Status
(Complete)
Last Modified 4/4/25
Period of Performance
9/15/23
Start Date
8/31/25
End Date
Funding Split
$1.0M
Federal Obligation
$0.0
Non-Federal Obligation
$1.0M
Total Obligated
Activity Timeline
Transaction History
Modifications to 2242216
Additional Detail
Award ID FAIN
2242216
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
FMCEN5SWM8L3
Awardee CAGE
7R2L9
Performance District
CA-16
Senators
Dianne Feinstein
Alejandro Padilla
Alejandro Padilla
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) | $999,407 | 100% |
Modified: 4/4/25