Local planning for autonomous navigation based on forward prediction and motion primitives pruning
Xingzhi Fu · Applied and Computational Engineering · 2023
This paper discusses the problem of local path planning for autonomous vehicles. This article introduces pruning strategies and their related map construction and data processing. Next, a forward path planning strategy was introduced, and a universally applicable path selection method was provided. The value of forward prediction strategy for autonomous driving technology was demonstrated by comparing it with ordinary mobile robot path planning algorithms. Then, the optimization of the forward paths through a pruning strategy reduced the time required for updating data by the algorithm introduced in the article. This article refers to the data provided in two literatures, compares and analyzes the advantages and disadvantages of two path planning schemes, and attempts to combine some of their advantages. At the end of this article, the calculation results based on MATLAB mathematical modeling are provided, and the rationality analysis of this path planning strategy is provided as well. Based on these analyses, this article provides suggestions for optimizing path planning algorithms.