一种移动机器人的路径规划算法研究

Study on Path Planning Method for Mobile Robot

针对移动机器人路径规划过程中存在易陷入局部最优、规划质量差和规划效率低等问题,提出一种结合入侵杂草算法和NURBS算法的混合路径规划方法。首先,根据路径规划要求建立目标函数,并将规划问题转化为函数最小值求解问题。然后,利用目标函数来指导入侵杂草算法寻找安全可行的路径点,接着将NURBS算法作为局部路径优化算子光滑处理路径,缩短路径长度。最后,在仿真环境下进行对比分析。结果表明,该方法相比于传统的入侵杂草算法在路径质量和效率上均有所提高,对实际移动机器人路径规划研究具有较高指导作用。

A imed at the problem that mobile robot path planning is easily trapped into local minimum and lacks in improving the quality and efficiency, a path planning method based on invasive weed optimization and NURBS is presented. Firstly, a feasible objective function was conducted according to the aim of path planning, and the problem of path planning was transformed into a minimization problem. Thereafter, invasive weed optimization was used to finding a sequence of safe and feasible path points under the guiding of objective function, while the NURBS-based local path optimizer was applied to smooth and shorten the path. Finally, contrast experiment was conducted in the simulation environment. The results show that the presented method improves the quality and efficiency of path planning compared with pure invasive weed optimization, which has higher guidance for the real path planning of mobile robots.