Principles and Algorithms for Natural and Engineered Systems

Abstract

The PI, P. S. Krishnaprasad, and co-PI, Andrea Cavagna, joined forces in a program of experimental, theoretical and computational investigation to uncover the fundamental principles that govern collective phenomena in three dimensions (3D). The investigations considered phenomena at two ends of length scale: (a) Birds flocking in a species of starling; and (b) Insects swarming in a species of midge. A primary objective of this project was to uncover order and structure in such biological collectives, model the observed behavior, extract control laws at the individual level that govern collective behavior, and seek technological benefits (in applications to collective robotics) from this research. The experimental program yielded new observations of starlings and midges in natural settings with higher temporal resolution than achieved before. The new data was analyzed by the Rome group via a series of computer vision based algorithms (segmentation, static matching, dynamic matching, static 3D-reconstruction, cluster analysis, stereo tracking 3D reconstruction), and theoretical principles shaped by statistical physics. The theoretical program in Maryland yielded new results on certain key, network motifs (based on motion camouflage pursuit or parallel navigation, and constant bearing pursuit) to serve as fundamental building block models of complex collective behavior. The results in this direction include stability classification of dynamical interactions, extensions to 3D, symmetry reduction and phase portraits, top-down analysis based on configuration space methods, variational principles and robotic demonstrations. New control-theoretic algorithms for smoothing and curvature law extraction for trajectories were tested on starling data provided by the Co-PI.

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Document Details

Document Type
Technical Report
Publication Date
Dec 16, 2014
Accession Number
ADA619896

Entities

People

  • Perinkulam S. Krishnaprasad

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Weapons Technologies

DTIC Thesaurus Topics

  • Animal Behavior
  • Birds
  • Collision Avoidance
  • Complex Systems
  • Computational Science
  • Computer Vision
  • Data Acquisition
  • Data Analysis
  • Databases
  • Geometry
  • Image Processing
  • Information Science
  • Information Systems
  • Mechanics
  • Military Research
  • Subatomic Particles
  • Three Dimensional

Readers

  • Computational Fluid Dynamics (CFD)
  • Computer Vision.
  • Control Systems Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control
  • Space
  • Space - Spacecraft Maneuvers