Abstract: For the path planning of mobile welding robots, the fast traversing random tree (RRT) algorithm has a long search time, is prone to generating winding paths, and has poor obstacle avoidance performance, and the time elastic band (TEB) algorithm has shortcomings such as speed output jumps, a fusion algorithm for mobile welding robot path planning with improved RRT and TEB was proposed. The purposeful extension and key point extraction strategies were introduced to improve the RRT algorithm, and enhance its search efficiency and smoothness in path planning. Furthermore, a minimum safety distance was introduced to improve the TEB algorithm,which enabled the mobile welding robot to effectively avoid obstacles, while increasing the constraint of target points on speed and reducing the impact on the mobile welding robot. The fusion of improved RRT and TEB algorithms enabled mobile welding robots to dynamically plan paths, and to avoid interference from dynamic obstacles, and simulation and physical experiments was conducted to verify it. The results demonstrate that the improved RRT algorithm reduces path search time by 58. 84%, and decreases the number of path inflection points by 73. 33%. The fusion of improved RRT and TEB algorithms can increase the safe distance between the mobile welding robot and obstacles by 50%, providing sufficient speed buffering time before reaching the target point, greatly improving the stability and obstacle avoidance ability of the mobile welding robot.