Grid Map Construction and Terrain Prediction for Quadruped Robot Based on C-Terrain Path

In general, grid map based path planning algorithms are employed in the robotics arena. The algorithm uses a grid map to represent environmental information, standardized. Compared with feature maps and topological maps, the algorithm realizes the construction of environmental maps in a more direct way, and has the characteristics of fast, simple and efficient.The integration and prediction of terrain is an unavoidable problem and the traditional raster map prediction method is based on the research of the terrain data itself, and lacks dynamic supplement for the path planning process. When the environmental data changes, the classification algorithm can only be re-executed, and the past data is completely discarded. Since the planned path is unlikely to change, the terrain tends to be stable. To solve this problem, this paper proposes a concept of C(circular)-terrain band following path nodes and terrain construction and prediction methods. The C-Terrain method first obtains an ordered set of passing points at the initial moment, based on the complete path planning. Then an ordered sequence of influence function values is obtained, which depends on the selection of the terrain band and the adjustment of related parameters. Finally, regression methods such as machine learning are used to complete the prediction of the path and location terrain, and the unknown path and terrain are predicted. The experimental results prove the accuracy and practical value of the C-T method.