Aiming at the shortcomings of slow convergence speed, unsmooth path and easy to fall into local optimum in Ant Colony System(ACS) algorithm, an ACS algorithm based on gravitational search strategy is proposed. Firstly, in order to solve the problem that the lack of map information in the initial stage of the algorithm leads to the great blindness problem of ant colony algorithm, a simplified ant colony algorithm is proposed to update the initial pheromone concentration; secondly, the search strategy of gravity algorithm is introduced to improve the speed of the later algorithm and effectively solve the local optimal problem; finally, the optimal path obtained by each iteration is optimized, which reduces the number of turning points and improves the smoothness of the path. Simulation results show that the improved algorithm can effectively improve the convergence speed and path smoothness of the algorithm. Additionally, the improved algorithm is applied to the actual mobile robot navigation experiment. The experimental results show that the improved algorithm can effectively solve the path planning problem of mobile robot, and effectively improve the efficiency of robot navigation.