Symmetry and reduction in collectives: low-dimensional cyclic pursuit

Abstract

We investigate low-dimensional examples of cyclic pursuit in a collective, wherein each agent employs a constant bearing (CB) steering law relative to exactly one other agent. For the case of three agents in the plane, we characterize relative equilibria and pure shape equilibria of associated closed-loop dynamics. Re-scaling time yields a reduction of phase space to two dimensions and effective tools for stability analysis. Study of bifurcation of a family of collinear equilibria dependent on a single CB control parameter reveals the presence of a rich collection of trajectories that are periodic in shape and undergo precession in physical space. For collectives in three dimensions, with an appropriate notion of CB pursuit strategy and corresponding steering law, the two-agent case proves to be explicitly integrable. These results suggest control schemes for small teams of mobile robotic agents engaged in area coverage tasks such as search and rescue, and raise interesting possibilities for behaviour in biological contexts.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 01, 2016
Source ID
10.1098/rspa.2016.0465

Entities

People

  • Eric W. Justh
  • Kevin S Galloway
  • P.S.Krishnaprasad

Organizations

  • Air Force Office of Scientific Research
  • Army Research Office
  • Northrop Grumman
  • Office of Naval Research
  • United States Naval Academy
  • United States Naval Research Laboratory
  • University of Maryland

Tags

Readers

  • Control Systems Engineering.
  • Critical Infrastructure Protection in CBRN and WMD Threats.
  • Neural Network Machine Learning.

Technology Areas

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