In order to solve the problems of slow path planning speed, insufficient path safety and oscillation of motion speed in the autonomous navigation process of measurement robots in complex building decoration scenarios, a combined navigation path planning method that improves A * and optimizes TEB is proposed. To enhance the safety and effectiveness of the path planning for architectural measurement robots, collision evaluation detection for obstacles has been introduced. Additionally, redundant path points and unnecessary turning points in the global planning path have been optimized. The optimized TEB algorithm is employed for local planning between adjacent path points, achieving optimal path planning and improving the safety performance of the path while reducing planning time and minimizing path turning angles. The experimental results show that the improved A * algorithm reduces the path length by 23.51% on average and is 42.52% faster on average than the traditional A * algorithm in terms of planning time, and the addition of the optimized TEB algorithm achieves local path correction to achieve dynamic obstacle avoidance, which verifies the safety and effectiveness of the algorithm.