SBIR/STTR Research Award

REAL-TIME OBJECT AND ROBOT END-EFFECTOR TRACKING SYSTEM

Award identifier 7f8b7f2e7a75dcb3a67f56a611832c4d6da7712c7830e600d3598b55cd9b90c6Awarding agency National Aeronautics and Space Administration

Award amount

$49,835

Program and phase

SBIR · Phase I

Award year

1991

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
National Aeronautics and Space Administration
Branch
Not reported
Recipient company
Kms Fusion Inc
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
Not reported
Topic code
Not reported

Research abstract

REAL-TIME, THREE-DIMENSIONAL OBJECT TRACKING IS THE KEY TO SUCCESSFULLY COMPLETING ROBOTIC END-EFFECTOR DOCKING TASKS IN UNCERTAIN AND CHANGEABLE ENVIRONMENTS. SINCE RELIABLE SYSTEMS FOR TRACKING THREE-DIMENSIONAL OBJECTS UNDER REALISTIC CONDITIONS DO NOT YET EXIST, THIS PROJECT PROPOSES TO DESIGN A REAL-TIME OBJECT AND ROBOTIC END-EFFECTOR TRACKING SYSTEM (RORETS). RORETS IS CENTERED ON A RECENTLY DISCOVERED APPROACH TO ESTIMATE THE POSITION AND ORIENTATION (POSE) OF ARBITRARILY SHAPED, PARTIALLY VISIBLE THREE-DIMENSIONAL OBJECTS IN A SINGLE, CLUTTERED, NOISY IMAGE. TO ATTAIN REAL-TIME PERFORMANCE, THE FIRM HAS REFORMULATED THE THEORY BEHIND THE POSE ESTIMATOR AND ADAPTED A NEW REPRESENTATION OF THREE-DIMENSIONAL OBJECTS THAT ALLOWS READY PREDICTION OF THE APPEARANCE OF EDGE CONTOURS FROM ANY VIEWPOINT, WITH APPROPRIATE HARDWARE THESE INNOVATIONS, COUPLED WITH A REAL-TIME IMPLEMENTATION OF A KALMAN FILTER FOR ESTIMATING AN OBJECTS' MOTION PARAMETERS, WILL ALLOW RORETS TO ACHIEVE REAL-TIME TRACKING PERFORMANCE. REAL-TIME, THREE-DIMENSIONAL OBJECT TRACKING IS THE KEY TO SUCCESSFULLY COMPLETING ROBOTIC END-EFFECTOR DOCKING TASKS IN UNCERTAIN AND CHANGEABLE ENVIRONMENTS. SINCE RELIABLE SYSTEMS FOR TRACKING THREE-DIMENSIONAL OBJECTS UNDER REALISTIC CONDITIONS DO NOT YET EXIST, THIS PROJECT PROPOSES TO DESIGN A REAL-TIME OBJECT AND ROBOTIC END-EFFECTOR TRACKING SYSTEM (RORETS). RORETS IS CENTERED ON A RECENTLY DISCOVERED APPROACH TO ESTIMATE THE POSITION AND ORIENTATION (POSE) OF ARBITRARILY SHAPED, PARTIALLY VISIBLE THREE-DIMENSIONAL OBJECTS IN A SINGLE, CLUTTERED, NOISY IMAGE. TO ATTAIN REAL-TIME PERFORMANCE, THE FIRM HAS REFORMULATED THE THEORY BEHIND THE POSE ESTIMATOR AND ADAPTED A NEW REPRESENTATION OF THREE-DIMENSIONAL OBJECTS THAT ALLOWS READY PREDICTION OF THE APPEARANCE OF EDGE CONTOURS FROM ANY VIEWPOINT, WITH APPROPRIATE HARDWARE THESE INNOVATIONS, COUPLED WITH A REAL-TIME IMPLEMENTATION OF A KALMAN FILTER FOR ESTIMATING AN OBJECTS' MOTION PARAMETERS, WILL ALLOW RORETS TO ACHIEVE REAL-TIME TRACKING PERFORMANCE.

Technology keywords

Not reported

Agency intelligence

National Aeronautics and Space Administration

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.