Multi-sensor Detection and Tracking using Traversability Based Prediction

Award Information
Agency:
Department of Defense
Branch
Defense Advanced Research Projects Agency
Amount:
$98,923.00
Award Year:
2009
Program:
SBIR
Phase:
Phase I
Contract:
W31P4Q-09-C-0442
Award Id:
91768
Agency Tracking Number:
08SB2-0557
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
814 W. Diamond Ave., Suite 301, Gaithersburg, MD, 20878
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
121257443
Principal Investigator:
Alberto Lacaze
President
(240) 631-0008
lacaze@roboticresearch.com
Business Contact:
Alberto Lacaze
President
(240) 631-0008
lacaze@roboticresearch.com
Research Institution:
n/a
Abstract
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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