Underwater digital elevation map gridding method based on optimal partition of suitable matching area

Abstract

Global positioning system signal does not penetrate into the water volume, and autonomous underwater vehicle have to use the inertial navigation system that will cause an inevitable cumulative error. Terrain reference position can zero out the inertial navigation system error and have been widely used. To improve the positioning accuracy, the planning path of the underwater robot is required to pass through the suitable matching areas in the path planning stage. So, a gridding map is needed to quantify the suitability of the terrain and to partition the suitable matching area and the unsuitable matching area optimally. In this article, we will focus on the quantitative method of terrain suitability and the grid parameter solution method for optimal partition of suitable matching area. Finally, the validity of the algorithm is obtained using the ship borne data. The results show that in the low suitability blocks, the influence of measurement error on terrain reference position accuracy is higher than that in high suitability blocks. And the average of terrain reference position deviation obtained of the path passed through the high suitability area is 53.3% which is lower than that of the path passed through the low suitability area, and the standard deviation of the position deviation is reduced by 21.15%.

An evaluation of path-planning methods for autonomous underwater vehicle based on terrain-aided navigation

“…Since the accuracy of TAN positioning is related to the complexity of the terrain, the terrain information around the path becomes the biggest factor to consider at this time. 9 We introduce the amount of Fisher information to measure complexity of the terrain. Define the amount of terrain Fisher information in a local area as follows 11…”

“…Since the accuracy of TAN positioning is related to the complexity of the terrain, the terrain information around the path becomes the biggest factor to consider at this time. 9…”

“…The goal is to find an optimal path from the start point to the end point according to a preset evaluation function under different environmental conditions. For TAN, its location is accurately related to terrain complexity, 9 the path-planning algorithm needs to consider both terrain complexity and motion characteristics of the AUVs.…”

An Adaptive Two-Dimensional Voxel Terrain Mapping Method for Structured Environment

“…Currently, the perception of the surrounding environment by mobile robots predominantly relies on depth cameras or Lidar sensors to model their environment. These sensors capture point cloud data from the environment, which, when combined with the robot's pose information, is used to generate raster maps [10][11][12], elevation maps [13][14][15], or threedimensional point cloud maps [16][17][18]. Generally, for legged mobile robots, landing point planning and motion control can be achieved using low-dimensional representations, eliminating the need for full three-dimensional space maps.…”