Abstract
Significant attention has been given to the field of multi-agent systems in recent years due to its potential to solve complex problems that cannot be addressed by a single agent. One such problem is the cooperative search and coverage application, which requires multiple agents to efficiently search and cover a given area. However, the effectiveness of such systems is dependent on various factors, including mission definition parameters and the approach used to achieve mission performance optimality. In this paper, an optimal strategy for segregating multi-agent missions for search and coverage applications is proposed. The proposed strategy involves dividing a single mission into several simultaneous missions based on the optimal division of the environment that ensures system performance optimality while achieving a common goal. The mission area is divided into sub-areas, and each sub-area is assigned to specific agents to improve overall system performance. The effectiveness of the proposed strategy is demonstrated through simulations and relevant comparisons.