Competitive perimeter defense with a turret and a mobile vehicle

Frontiers in Control Engineering

Control Engineering

Eric Torng¹  David W. Casbeer²  Alexander Von Moll²  Shaunak D. Bopardikar³  Shivam Bajaj³ 

[1]Computer Science and Engineering Department, Michigan State University, East Lansing, MI, United States

[2]Control Science Center, Air Force Research Laboratory, Dayton, OH, United States

[3]Electrical and Computer Engineering Department, Michigan State University, East Lansing, MI, United States

关键词: online optimization;    perimeter defense;    competitive ratio;    pursuit evasion games;    dynamic vehicle routing;    cooperative agents;   

DOI  :  10.3389/fcteg.2023.1128597

 received in 2022-12-20, accepted in 2023-01-18,  发布年份 2023

来源: Frontiers

【 摘 要 】

We consider perimeter defense problem in a planar conical environment with two cooperative heterogeneous defenders, i.e., a turret and a mobile vehicle, that seek to defend a concentric perimeter against mobile intruders. Arbitrary numbers of intruders are released at the circumference of the environment at arbitrary time instants and locations. Upon release, they move radially inwards with fixed speed towards the perimeter. The defenders are heterogeneous in terms of their motion and capture capabilities. Specifically, the turret has a finite engagement range and can only turn (clockwise or anti-clockwise) in the environment with fixed angular rate whereas, the vehicle has a finite capture radius and can move in any direction with unit speed. We present a competitive analysis approach to this perimeter defense problem by measuring the performance of multiple cooperative online algorithms for the defenders against arbitrary inputs, relative to an optimal offline algorithm that has information about the entire input sequence in advance. Specifically, we establish necessary conditions on the parameter space to guarantee finite competitiveness of any online algorithm. We then design and analyze four cooperative online algorithms and characterize parameter regimes in which they have finite competitive ratios. In particular, our first two algorithms are 1-competitive in specific parameter regimes, our third algorithm exhibits different competitive ratios in different regimes of problem parameters, and our fourth algorithm is 1.5-competitive in specific parameter regimes. Finally, we provide multiple numerical plots in the parameter space to reveal additional insights into the relative performance of our algorithms.

【 授权许可】

Unknown   
Copyright © 2023 Bajaj, Bopardikar, Moll, Torng and Casbeer.