Abstract: The performances of wireless sensor network heavily depend on topology which is formed by sensor nodes’ deployment. In order to increase coverage area of Wireless Sensor Network, decrease redeploying times and energy consumption, a novel coverage algorithm named CSAPO was proposed in this study. CSAPO deployment strategy was designed through combining artificial physics optimization algorithm and clonal selection algorithm, where the movement direction of particle is together determined by artificial physics optimization and clonal selection algorithm. In this research, Artificial physics optimization was devoted to update the main motivation and the clonal selection algorithm was used to help artificial physics optimization to avoid trapping local optimum. Simulation results showed that performances of algorithms such as final coverage rate, convergence speed and total moving distance are improved significantly compared with artificial physics optimization and particle swarm optimization. At last, the impact of mutation constant Cm on performances was analyzed.