  This paper provides a new solution approach to a multi-player perimeter
defense game, in which the intruders' team tries to enter the territory, and a
team of defenders protects the territory by capturing intruders on the
perimeter of the territory. The objective of the defenders is to detect and
capture the intruders before the intruders enter the territory. Each defender
independently senses the intruder and computes his trajectory to capture the
assigned intruders in a cooperative fashion. The intruder is estimated to reach
a specific location on the perimeter at a specific time. Each intruder is
viewed as a spatio-temporal task, and the defenders are assigned to execute
these spatio-temporal tasks. At any given time, the perimeter defense problem
is converted into a Decentralized Multi-UAV Spatio-Temporal Multi-Task
Allocation (DMUST-MTA) problem. The cost of executing a task for a trajectory
is defined by a composite cost function of both the spatial and temporal
components. In this paper, a decentralized consensus-based bundle algorithm has
been modified to solve the spatio-temporal multi-task allocation problem, and
the performance evaluation of the proposed approach is carried out based on
Monte-Carlo simulations. The simulation results show the effectiveness of the
proposed approach to solve the perimeter defense game under different
scenarios. Performance comparison with a state-of-the-art centralized approach
with full observability, clearly indicates that DMUST-MTA achieves similar
performance in a decentralized way with partial observability conditions with a
lesser computational time and easy scaling up.
