Mobile Wireless Sensor Networks (MWSNs) play a pivotal role in applications such as environmental monitoring, disaster response, and search-and-rescue missions. Ensuring robust communication and efficient navigation in such networks is critical for coordinated task completion in dynamic and complex environments. This paper introduces a novel Particle Swarm Optimization (PSO)-based strategy tailored for MWSNs, enabling mobile nodes to maintain reliable network connectivity, avoid obstacles, and efficiently reach target destinations. By integrating real-time link quality assessment using Rician fading models with dynamic position optimization, the proposed method ensures robust performance under varying obstacle densities and interference levels. Simulation results demonstrate its effectiveness in achieving high communication reliability and safe navigation, significantly outperforming traditional methods. This approach highlights its adaptability and scalability, making it a valuable solution for enhancing the functionality of MWSNs in real-world scenarios.