With the advent of Wireless Power Transfer (WPT) technology, Wireless Rechargeable Sensor Networks (WRSNs) have emerged as a promising solution for prolonging the lifespan of wireless sensor networks. However, in practical scenarios, obstacles are pervasive within WRSNs. Previous studies often assume that obstacles invariably weaken signal strength and therefore disregard their impact for the sake of computational ease. This presumption contradicts fundamental signal propagation principles, rendering these methods impractical for real-world applications. In this section, we explore the wireless signal propagation process and present a theoretical charging model designed to enhance charging efficiency by leveraging obstacles. By applying the concept of Fresnel Zones (FZs), we reformulate the wireless charging model and discretize the charging power to pinpoint optimal charging locations and times. We frame the problem of maximizing charging efficiency (EMO) in the presence of obstacles as a submodular function maximization problem and propose a cost-effective algorithm to address it. Ultimately, test-bed experiments and simulations show that our approaches outperform comparison algorithms by at least 10% in terms of improved charging efficiency.