TempFuser: Learning Agile, Tactical, and Acrobatic Flight Maneuvers Using a Long Short-Term Temporal Fusion Transformer
Dogfighting is a challenging scenario in aerial applications that requires a comprehensive understanding of both strategic maneuvers and the aerodynamics of agile aircraft. The aerial agent needs to not only understand tactically evolving maneuvers of fighter jets from a long-term perspective but al...
Saved in:
Main Authors | , |
---|---|
Format | Journal Article |
Language | English |
Published |
06.08.2023
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Dogfighting is a challenging scenario in aerial applications that requires a
comprehensive understanding of both strategic maneuvers and the aerodynamics of
agile aircraft. The aerial agent needs to not only understand tactically
evolving maneuvers of fighter jets from a long-term perspective but also react
to rapidly changing aerodynamics of aircraft from a short-term viewpoint. In
this paper, we introduce TempFuser, a novel long short-term temporal fusion
transformer architecture that can learn agile, tactical, and acrobatic flight
maneuvers in complex dogfight problems. Our approach integrates two distinct
temporal transition embeddings into a transformer-based network to
comprehensively capture both the long-term tactics and short-term agility of
aerial agents. By incorporating these perspectives, our policy network
generates end-to-end flight commands that secure dominant positions over the
long term and effectively outmaneuver agile opponents. After training in a
high-fidelity flight simulator, our model successfully learns to execute
strategic maneuvers, outperforming baseline policy models against various types
of opponent aircraft. Notably, our model exhibits human-like acrobatic
maneuvers even when facing adversaries with superior specifications, all
without relying on prior knowledge. Moreover, it demonstrates robust pursuit
performance in challenging supersonic and low-altitude situations. Demo videos
are available at https://sites.google.com/view/tempfuser. |
---|---|
DOI: | 10.48550/arxiv.2308.03257 |