Multi-sensor Detection and Tracking using Traversability Based Prediction

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-09-C-0442
Agency Tracking Number: 08SB2-0557
Amount: $98,923.00
Phase: Phase I
Program: SBIR
Awards Year: 2009
Solicitation Year: 2008
Solicitation Topic Code: SB082-029
Solicitation Number: 2008.2
Small Business Information
814 W. Diamond Ave., Suite 301, Gaithersburg, MD, 20878
DUNS: 121257443
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: Y
Principal Investigator
 Alberto Lacaze
 (240) 631-0008
Business Contact
 Alberto Lacaze
Title: President
Phone: (240) 631-0008
Research Institution
In order for fully autonomous robots to be integrated effectively into small combat teams, unmanned ground vehicles (UGVs) must maneuver safely and intelligently among military ground forces and non-combatants. To achieve such robust obstacle detection capability in unstructured environments, it is necessary to fuse information from various sensor modalities. Under various programs in the past, our team has developed obstacle detection/tracking capabilities using Ladar, LWIR and a visible light camera. The team created by Robotic Research, LLC (RR) and General Dynamics Robotic Systems (GDRS) provides a unique set of expertise and on the field experience that cannot be matched in the industry. Kalman filters are the most common approach for tracking and prediction of obstacles but are extremely limited in complex environments. The TACTIC prediction system will drastically increase the efficacy of tracking behind occlusions and in highly cluttered terrain. Our team has the exclusive capability to leverage detection algorithms, planning algorithms, simulation environments, and actual robotic vehicles that are required to make this project a success.

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

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