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.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2004
Accession Number
ADA433221

Entities

People

  • Allen R. Tannenbaum
  • Anthony J. Calise
  • Cole Gilbert
  • J. E. Corban

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Collision Avoidance
  • Computational Science
  • Computer Vision
  • Computers
  • Control Systems
  • Fluid Dynamics
  • Geometry
  • Guidance
  • Image Processing
  • Image Registration
  • Image Segmentation
  • Kalman Filters
  • Navigation
  • Proportional Navigation
  • Three Dimensional
  • Trajectories

Readers

  • Military History / Militaries and War Studies
  • Nanocomposite Materials Science
  • Sensor Fusion and Tracking Systems.