Realtime Determination and Prediction of Aircraft Trajectories Using Limited Sensor Data

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-09-C-0594
Agency Tracking Number: N09A-005-0521
Amount: $69,450.00
Phase: Phase I
Program: STTR
Awards Year: 2009
Solicitation Year: 2009
Solicitation Topic Code: N09-T005
Solicitation Number: 2009.A
Small Business Information
PO Box 202, West End of Second Street, Essington, PA, 19029
DUNS: 793042243
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jim Hacunda
 Director, Systems Engineering
 (610) 521-6115
 JimHacunda@DragonflyPictures.com
Business Contact
 Gregory Piasecki
Title: Driector, Commercialization
Phone: (610) 521-6115
Email: 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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