SCAFLE - Self Calibrating, Adaptive, Fused LIDAR/EO Sensor

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-11-M-0320
Agency Tracking Number: N11A-020-0327
Amount: $79,984.00
Phase: Phase I
Program: STTR
Awards Year: 2011
Solicitation Year: 2011
Solicitation Topic Code: N11A-T020
Solicitation Number: 2011.A
Small Business Information
555 Quince Orchard Road, Suite 300, Gaithersburg, MD, -
DUNS: 121257443
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: Y
Principal Investigator
 Karl Kluge
 Senior Engineer
 (240) 631-0008
Business Contact
 Alberto Lacaze
Title: President
Phone: (240) 631-0008
Research Institution
 Jet Propulsion Laboratory
 Douglas Gilbertson
 4800 Oak Grove Drive
Pasadena, CA, 91109-
 (818) 393-3458
 Federally funded R&D center (FFRDC)
The ability to fuse electro-optical (EO) imagery with range data enhances the robustness of unmanned ground vehicle (UGV) autonomy by allowing discrimination between types of terrain that cannot be distinguished on the basis of geometry alone (non-traversable mud vs. dry soil, non-traversable rocks vs. traversable brush, etc.). Performing this fusion requires knowing both the intrinsic (optical center, focal length, etc.) and extrinsic (relative offset and orientation) calibration parameters of the sensors. These can vary over time as sensors are replaced due to damage, the system is jolted during use, etc. In order to be practical for warfighter use, such a fused sensor system needs to be able to self-calibrate using features of the environment, and to adaptively update that calibration as shock or other sources of variation cause it to change. Such adaptive self-calibration avoids the need to train warfighters in calibration procedures, and eliminates the need for additional equipment. We propose designing a compact, low-cost Self-Calibrating (Adaptive) Fusion of LADAR and EO imagery (SCAFLE) sensor that will provide fused visible multi-spectral EO and LADAR range data covering a full 360 degree field of regard to support perception capabilities such as terrain classification and visual odometry.

* Information listed above is at the time of submission. *

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