Abstract:Path planning is an important part of realizing robot autonomous movement. The planned path largely determine the performance of the robot in work. Traditional path planning algorithms, such as the dijkstra algorithm which is based on graph search and it"s improved version the A^* algorithm, as well as the sampling-based RRT algorithm and it"s improved version RRT* algorithm, only consider obstacle avoidance problem; Algorithms which based on interpolation curves can generate smoother trajectories. Algorithms which based on numerical optimization can add robot speed, acceleration, etc. to the loss function, can generate trajectories with better dynamic properties through optimial solving. In current, topographic information are richer and more accurate, few algorithms can make full use of them. Based on the digital elevation map (DEM) of the seabed, this paper proposed extended A* algorithm and improved FM algorithm, which can use prior geographic information to improve the effect of path planning. Through simulation analysis, three algorithms are compared: extended A* algorithm, TC FM and TC FM* algorithm, simulations show that extended A* algorithm solves faster, the local planning ability is stronger, and the TC FM and TC FM* algorithm find the path shorter and smoother.