In this letter, an efficient motion planning approach with grid-based generalized Voronoi diagrams is newly proposed for mobile robots. Different from existing approaches, the novelty of this work is twofold: 1) a new state lattice-based path searching approach is proposed, in which the search space is reduced to a Voronoi corridor to further improve the search efficiency, along with a Voronoi potential field constructed to make the searched path keep a reasonable distance from obstacles to provide sufficient optimization margin for the subsequent path smoothing, and 2) an efficient quadratic programming-based path smoothing approach is presented, wherein the clearance to obstacles is considered in the form of the penalty of the deviation from the safe reference path to improve the path clearance of hard-constrained path smoothing approaches. We validate the efficiency and smoothness of our approach in various challenging simulation scenarios and large-scale outdoor environments. It is shown that the computational efficiency is improved by 17.1% in the path searching stage, and smoothing the path with our approach is 11.86 times faster than a recent gradient-based path smoothing approach. We will release the source code to the robotics community.

翻译：在本信内,为移动机器人提出了基于网格的通用Voronoi图表的高效运动规划方法,与现有方法不同,这项工作的新颖之处是双重的:1)提出一个新的基于固定路径的搜索方法,其中搜索空间缩小为Voronoi走廊,以进一步提高搜索效率,同时建立一个Voronoi潜在场地,使搜索路径与障碍保持合理的距离,为随后的通畅道路提供足够的优化空间;2)提出一种高效的四边式编程平滑方法,其中认为清除障碍是对偏离安全参考路径的处罚,以更好地清除难以控制的道路平滑方法。我们将验证我们在各种具有挑战性的模拟情景和大规模户外环境中采用的方法的效率和顺利性。我们表明,在搜索路径的阶段,计算效率提高了17.1%,用我们的方法平滑的路径比最近采用的基于梯度的平滑路径快11.86倍。我们将将源代码释放给机器人界。