Evolving cooperative strategies for UAV teams

We present a Genetic Programming approach to evolve cooperative controllers for teams of UAVs. Our focus is a collaborative search mission in an uncertain and/or hostile environment. The controllers are decision trees constructed from a set of low-level functions. Evolved decision trees are robust to changes in initial mission parameters and approach the optimal bound for time-to-completion. We compare results between steady-state and generational approaches, and examine the effects of two common selection operators.

[1]  L. Darrell Whitley,et al.  The GENITOR Algorithm and Selection Pressure: Why Rank-Based Allocation of Reproductive Trials is Best , 1989, ICGA.

[2]  G.J. Barlow,et al.  Incremental evolution of autonomous controllers for unmanned aerial vehicles using multi-objective genetic programming , 2004, IEEE Conference on Cybernetics and Intelligent Systems, 2004..

[3]  Magnus Snorrason,et al.  SEARCH PATH OPTIMIZATION FOR UAVS USING STOCHASTIC SAMPLING WITH ABSTRACT PATTERN DESCRIPTORS , 2003 .

[4]  N. Swamy,et al.  Finding a better-than-classical quantum AND/OR algorithm using genetic programming , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[5]  Sean Luke,et al.  Issues in Scaling Genetic Programming: Breeding Strategies, Tree Generation, and Bloat , 2000 .

[6]  Tina Yu,et al.  Performance-Enhanced Genetic Programming , 1997, Evolutionary Programming.

[7]  Alan C. Schultz,et al.  Heterogeneity in the Coevolved Behaviors of Mobile Robots: The Emergence of Specialists , 2001, IJCAI.

[8]  Lee Spector,et al.  Evolving teamwork and coordination with genetic programming , 1996 .

[9]  Frank W. Moore,et al.  A Methodology for Missile Countermeasures Optimization under Uncertainty , 2002, Evolutionary Computation.

[10]  Darrell Whitley,et al.  Genitor: a different genetic algorithm , 1988 .

[11]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[12]  Marco Zennaro,et al.  An architecture for UAV team control , 2004 .

[13]  D. Rathbun,et al.  An evolution based path planning algorithm for autonomous motion of a UAV through uncertain environments , 2002, Proceedings. The 21st Digital Avionics Systems Conference.

[14]  Tucker R. Balch,et al.  Behavior-based formation control for multirobot teams , 1998, IEEE Trans. Robotics Autom..

[15]  Marios M. Polycarpou,et al.  A cooperative search framework for distributed agents , 2001, Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206).

[16]  H. Van Dyke Parunak,et al.  DIGITAL PHEROMONES FOR AUTONOMOUS COORDINATION OF SWARMING UAV'S , 2002 .

[17]  Maja J. Mataric,et al.  Issues and approaches in the design of collective autonomous agents , 1995, Robotics Auton. Syst..

[18]  Sean Luke,et al.  Genetic Programming Produced Competitive Soccer Softbot Teams for RoboCup97 , 1998 .

[19]  Inman Harvey,et al.  Noise and the Reality Gap: The Use of Simulation in Evolutionary Robotics , 1995, ECAL.

[20]  Maja J. Mataric,et al.  Multi-robot target acquisition using multiple objective behavior coordination , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[21]  Izhak Rubin,et al.  A framework and analysis for cooperative search using UAV swarms , 2004, SAC '04.

[22]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.