Title:
Approaches to Vision-Based Formation Control
Approaches to Vision-Based Formation Control
Author(s)
Johnson, Eric N.
Calise, Anthony J.
Sattigeri, Ramachandra J.
Watanabe, Yoko
Madyastha, Venkatesh
Calise, Anthony J.
Sattigeri, Ramachandra J.
Watanabe, Yoko
Madyastha, Venkatesh
Advisor(s)
Editor(s)
Collections
Supplementary to
Permanent Link
Abstract
This paper implements several methods for
performing vision-based formation flight control of multiple
aircraft in the presence of obstacles. No information is
communicated between aircraft, and only passive 2-D vision
information is available to maintain formation. The methods
for formation control rely either on estimating the range from
2-D vision information by using Extended Kalman Filters or
directly regulating the size of the image subtended by a leader
aircraft on the image plane. When the image size is not a
reliable measurement, especially at large ranges, we consider
the use of bearing-only information. In this case, observability
with respect to the relative distance between vehicles is
accomplished by the design of a time-dependent formation
geometry. To improve the robustness of the estimation process
with respect to unknown leader aircraft acceleration, we
augment the EKF with an adaptive neural network. 2-D and
3-D simulation results are presented that illustrate the various
approaches.
Sponsor
This work was supported in part by AFOSR MURI #F49620-03-1-
0401: Active Vision Control Systems for Complex Adversarial 3-D
Environments.
Date Issued
2004-12
Extent
Resource Type
Text
Resource Subtype
Proceedings