Autonomous unmanned systems have numerous applications in a complex environment. One such application is coverage path planning to explore and cover a known or unknown area. The efficiency of such an application, especially for multi-agents, can be greatly increased by dividing the active area into an exclusive connected area of operation beforehand. Finding an equal division for the coverage path planning can be crucial to the performance of such operation. Therefore, we proposed an optimized region distribution method using Particle Swarm Optimization (PSO) that was modified with repulsion field and inspired by A* to find optimal base placement, and Spanning Tree Coverage (STC) with connectivity-conscious bidding to ensure equal distribution. The proposed method managed to achieve even distribution in an area with or without obstacle outperforming Rapidly Exploring Random Trees (RRT) and Centroid Veronoi Tesselation (CVT), and in an area with large amount of obstacle, managed to outpace both methods in term of iteration or average time.