(Georgia Institute of Technology, 2014-05)
Johnson, Eric N.; Mooney, John G.
This paper describes recent results to develop, improve, and flight test a multi-aircraft collaborative architecture, focused on decentralized autonomous decision-making. The architecture includes a search coverage algorithm, behavior estimation, and a pursuit algorithm designed to solve a scenario-driven challenge problem. The architecture was implemented on a pair of Yamaha RMAX helicopters outfitted with modular avionics, as well as an associated set of simulation tools. Simulation and flight test results for single- and multiple- aircraft scenarios are presented. Further work suggested includes identification and development of more sophisticated methods that can replace the simpler elements in modular fashion.
(Georgia Institute of Technology, 2010-08)
Christmann, Hans Claus; Johnson, Eric N.
The presented work introduces a graph based approach to model urban (or otherwise
cluttered) environments for UAS utilization beyond line-of-sight as well as out of direct
R/F range of the operator's control station. Making the assumption that some a priori data
of the environment is available, the proposed method uses a classification of obstacles with
respect to their impact on UAV motion and R/F communication and generates continuously
updateable graphs usable to compute traverseable paths for UAVs while maintaining R/F
communication.
Using a simulated urban scenario this work shows that the proposed modeling method
allows to find reachable loiter or hover areas for UAVs in order to establish a multi-hop
R/F communication link between a primary UAV and its remote operator by utilizing an
overlay of motion (Voronoi based) and R/F (visibility based) specific mapping methods.
(Georgia Institute of Technology, 2010-04)
Shah, Syed Irtiza Ali; Wu, Allen D.; Johnson, Eric N.
This paper develops a vision-based algorithm to detect a visual marker in real time and
in the presence of excessive colored noise for Unmanned Aerial Vehicles. After using various
image analysis techniques, including color histograms, filtering techniques and color space
analyses, typical pixel-based characteristics of the visual marker were established. It was
found that not only various color space based characteristics were significant, but also
relationships between various channels across different color spaces were of great
consequence. A block based search algorithm was then used to search for those established
characteristics in real-time image data stream from a colored camera. A low cost noise and
interference filter was also devised to handle excessive noise that was encountered during
flight tests. The specific implementation scenario is that of detection of a Blue LED for
GeorgiaTech's participating aircraft into the International Aerial Robotics competition.
The final algorithm that was implemented on GTAR lama aircraft, used both multiple
thresholding and linear confidence level calculations and was successfully used in the
competition in 2009.