优化蚁群算法在无人车自主导航中的应用

Application of Improved Ant Colony Algorithm to Autonomous Navigation of Unmanned Vehicles [HS)]

摘要:

由于蚁群算法规划的最优路径存在尖峰和折线,研究利用三阶贝塞尔曲线对蚁群算法进行优化,通过选择可靠的控制点来控制最优路径的整体趋势,从而消除路径上的尖峰并对折线进行平滑处理；将优化后的蚁群算法在无人车自主导航中进行了应用,结果证明优化后的蚁群算法可以为无人车实时规划出一条高质量的最优路径,最优路径不仅有效地避开了障碍物,而且有效消除路径上尖峰和折线。

Abstract:

Since spikes and the broken lines present in the optimal path planned by ant colony algorithm, utilize third-order Bezier curve to optimize the planning results of the ant colony algorithm, by selecting reliable control points control the overall trend of the optimal path, thus the spikes can be eliminated and the broken lines can be smoothed. The ant colony optimization algorithm for autonomous navigation of unmanned vehicles has been applied, the results prove that the optimized ant colony algorithm can receive the real-time planning of a high-quality optimal path for unmanned vehicles. It not only can effectively avoid the obstacles, but also can effectively eliminate the spikes and broken lines of the path.