Stochastic Patrolling and Collision Avoidance for Two UAVs in a Base Defense Scenario

This paper discusses the stochastic patrolling of a region under collision avoidance constraints by two UAVs. The patrol pattern is controlled by an algorithm that ensures weighted randomized coverage of the region in such a way as to patrol the entire region. The purpose is to search a region for an intruder by a pattern that is undetectable to the intruder. The algorithm ensures that the entire region is searched in an unpredictable way. Avoidance algorithms are implemented to adjust the trajectories of the UAVs in a relatively confined space. The control structure presented is hierarchical with operator-inthe-loop capability as well as lower level collision avoidance control to ensure safe guidance. Computational results are presented detailing the implementation of these algorithms on autonomous helicopters.

[1]  Zhi-Hong Mao,et al.  Stability and performance of intersecting aircraft flows under decentralized conflict avoidance rules , 2001, IEEE Trans. Intell. Transp. Syst..

[2]  Claire J. Tomlin,et al.  Decentralized cooperative collision avoidance for acceleration constrained vehicles , 2008, 2008 47th IEEE Conference on Decision and Control.

[3]  William B. Dunbar,et al.  Model predictive control of coordinated multi-vehicle formations , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[4]  Mario Innocenti,et al.  Autonomous formation flight , 2000 .

[5]  William B. Dunbar,et al.  Cooperative control of multi-vehicle systems using cost graphs and optimization , 2003, Proceedings of the 2003 American Control Conference, 2003..

[6]  Matt R. Jardin.  Ideal free flight through multiple aircraft neighboring optimal control , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[7]  J.K. Hedrick,et al.  Border patrol and surveillance missions using multiple unmanned air vehicles , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[8]  Claire J. Tomlin,et al.  Quadrotor Helicopter Flight Dynamics and Control: Theory and Experiment , 2007 .

[9]  Rodney Teo,et al.  Decentralized overlapping control of a formation of unmanned aerial vehicles , 2004, Autom..

[10]  J.B. de Sousa,et al.  Dynamic teams of networked vehicle systems , 2005, 2005 portuguese conference on artificial intelligence.

[11]  Jonathan P. How,et al.  COORDINATION AND CONTROL OF MULTIPLE UAVs , 2002 .

[12]  Lesley A. Weitz,et al.  Decentralized Cooperative-Control Design for Multivehicle Formations , 2007 .

[13]  Ed Williams.  Airborne Collision Avoidance System , 2004, SCS.

[14]  Jonathan P. How,et al.  Aircraft trajectory planning with collision avoidance using mixed integer linear programming , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[15]  F. Borrelli,et al.  Collision-free UAV formation flight using decentralized optimization and invariant sets , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[16]  S. Shankar Sastry,et al.  Conflict resolution for air traffic management: a study in multiagent hybrid systems , 1998, IEEE Trans. Autom. Control..

[17]  E. Frazzoli,et al.  Probabilistic verification of decentralized multi-agent control strategies: a Case Study in Conflict Avoidance , 2007, 2007 American Control Conference.

[18]  R. Olfati-Saber,et al.  Collision avoidance for multiple agent systems , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).