An improved ant colony optimization based on convex policy and the survival of the fittest strategy for robot path planning is proposed in this paper. This algorithm first use convex policy to process the robot's static workspace, and it can reduce the blindness of searching and the possibility of falling into the trap in environment. In addition, a survival of the fittest strategy is added in the ant colony optimization to further improve the performance of the algorithm time, optimum performance and robustness. Experimental results show that the improved ant colony optimization not only can overcome the defect of easy to fall into local optimal solution, but also can improve the operation efficiency.