Biological Inspired Direct Adaptive Guidance and Control for Autonomous Flight Systems

Abstract : The work at Cornell centered on developing experimental methods to characterize flesh fly pursuit evasions, and resulted in the maturation of effective means to capture the 3-D trajectory, as well as body and head orientation. The data was processed at first by hand, and later using image processing algorithms to develop 3-D visualizations at the track, including the head orientation, and ultimately to map the location of the target on the eye during the pursuit. The results provided a means to compare the guidance strategy of the fly with traditional proportional navigation, and to look for inspiration in the development of new guidance laws. Work was also completed to introduce clutter into the encounter. While a much greater understanding of the tracking and guidance strategy of the flesh fly was developed and documented, the work has not yet resulted in the discovery of a better alternative to traditional engineered guidance laws.