Moving Object Tracking Onboard a Moving Platform (MOTO-MP)

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-09-C-0490
Agency Tracking Number: 08SB2-0540
Amount: $98,154.00
Phase: Phase I
Program: SBIR
Awards Year: 2009
Solicitation Year: 2008
Solicitation Topic Code: SB082-029
Solicitation Number: 2008.2
Small Business Information
625 Mount Auburn Street, Cambridge, MA, 02138
DUNS: 115243701
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jonah McBride
 Scientist
 (617) 491-3474
 jmcbride@cra.com
Business Contact
 Gail Zaslow
Title: Contract Specialist
Phone: (617) 491-3474
Email: gzaslow@cra.com
Research Institution
N/A
Abstract
Mobile robots are a valuable asset to warfighters, keeping them out of harms way while remotely conducting dangerous bomb-disposal and reconnaissance missions. Autonomous and semi-autonomous operation of these robots would provide additional benefit by freeing up the attention of the operator for other tasks such as personal safety. It also increases usability and reduces training time. Thus far, efforts to develop automation have been limited to static environments. There is considerable resistance to autonomous operation in dynamic environments (which feature multiple humans, robots or vehicles) due to the risk of collision and other safety issues. We propose an approach for “Moving Object Tracking Onboard a Moving Platform”, or MOTO-MP. It enables a robot to detect and track multiple moving objects in a scene while in motion. Unlike traditional approaches which struggle to identify moving objects when the entire scene is in motion, MOTO-MP employs a simple but robust approach involving tracking in image space, an epipolar Hough space, and the 3D world space. A particle filter tracks clusters of moving features, rejecting false tracks, and a Kalman filter predicts the trajectory of objects in world space so that a robot’s navigation and path planning system can avoid collisions.

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

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