Realtime Determination and Prediction of Aircraft Trajectories Using Limited Sensor Data

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$69,450.00
Award Year:
2009
Program:
STTR
Phase:
Phase I
Contract:
N68335-09-C-0594
Award Id:
90261
Agency Tracking Number:
N09A-005-0521
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
PO Box 202, West End of Second Street, Essington, PA, 19029
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
793042243
Principal Investigator:
Jim Hacunda
Director, Systems Engineering
(610) 521-6115
JimHacunda@DragonflyPictures.com
Business Contact:
Gregory Piasecki
Driector, Commercialization
(610) 521-6115
GregoryPiasecki@DragonflyPictures.com
Research Institution:
University of Pennsylvania
Maxim Likhachev
GRASP Laboratory, Levine Hall
3330 Walnut Street
Philadelphia, PA, 19104 6228
(215) 746-2097
Nonprofit college or university
Abstract
Dragonfly Pictures, Inc. (DPI) and UPENN propose to develop a novel real-time trajectory prediction tool called Trajectory Tree Prediction Planner (TTPP). TTPP is based on two ideas. First, since it is impossible to robustly predict a single trajectory of an aircraft if its full state and intent is unknown, we advocate generating a set (tree) of trajectories. Each of the trajectories will be associated with the probability of occurrence, and the cumulative probability of predicted trajectories will be near one. Second, while the prediction of multiple trajectories will be even more computationally expensive than the prediction of a single trajectory, we will generate these trajectories using our previously developed incremental planning algorithms (e.g., D* Lite, Anytime D*, Adaptive A*). These algorithms are specifically designed for solving repeated planning problems in real-time and compute the new paths orders of magnitude faster by re-using their previous planning efforts. These algorithms have been shown to work well on various unmanned ground and air vehicles and will therefore be well-suited to the problem of generating the tree of future trajectories in real-time.

* information listed above is at the time of submission.

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