Abstract: To address unreasonable trajectory evaluation selection and low obstacle avoidance efficiency problems of the dynamic window approach (DWA) used in obstacle scenes of building construction, we propose a static and dynamic local path planning method for robots based on integrating attraction-repulsion and DWA. First, we improve the constraint conditions of velocity sampling with and without obstacles for multi-obstacle environments. Second, we optimize the navigation evaluation function to increase the running speed. Finally, we propose an evaluation function to solve the unreasonable trajectory selection problem and optimize the obstacle avoidance evaluation function by combining repulsion thought. Experiment results in different environments show that the performance of the proposed algorithm, including iteration times, running time, and path length, can be optimized by 20 % approximately. The improvement in various performance indicators can reach more than 25 %, which solves the problems of unreasonable trajectory evaluation selection and low obstacle avoidance efficiency in the original and improved DWAs in complex obstacle environments.