A biologically inspired approach to modeling unmanned vehicle teams

Roger S. Cortesi; Kevin S. Galloway; Eric W. Justh

doi:10.1117/12.778373

1 May 2008 A biologically inspired approach to modeling unmanned vehicle teams

Roger S. Cortesi, Kevin S. Galloway, Eric W. Justh

Proceedings Volume 6964, Evolutionary and Bio-Inspired Computation: Theory and Applications II; 696405 (2008) https://doi.org/10.1117/12.778373
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

Cooperative motion control of teams of agile unmanned vehicles presents modeling challenges at several levels. The "microscopic equations" describing individual vehicle dynamics and their interaction with the environment may be known fairly precisely, but are generally too complicated to yield qualitative insights at the level of multi-vehicle trajectory coordination. Interacting particle models are suitable for coordinating trajectories, but require care to ensure that individual vehicles are not driven in a "costly" manner. From the point of view of the cooperative motion controller, the individual vehicle autopilots serve to "shape" the microscopic equations, and we have been exploring the interplay between autopilots and cooperative motion controllers using a multivehicle hardware-in-the-loop simulator. Specifically, we seek refinements to interacting particle models in order to better describe observed behavior, without sacrificing qualitative understanding. A recent analogous example from biology involves introducing a fixed delay into a curvature-control-based feedback law for prey capture by an echolocating bat. This delay captures both neural processing time and the flight-dynamic response of the bat as it uses sensor-driven feedback. We propose a comparable approach for unmanned vehicle modeling; however, in contrast to the bat, with unmanned vehicles we have an additional freedom to modify the autopilot. Simulation results demonstrate the effectiveness of this biologically guided modeling approach.

Citation Download Citation

Roger S. Cortesi, Kevin S. Galloway, and Eric W. Justh "A biologically inspired approach to modeling unmanned vehicle teams", Proc. SPIE 6964, Evolutionary and Bio-Inspired Computation: Theory and Applications II, 696405 (1 May 2008); https://doi.org/10.1117/12.778373

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