计算机科学
路径(计算)
蚁群
数学优化
最短路径问题
作者
Yijing Wang,Xin Lu,Zhiqiang Zuo
出处
期刊:Chinese Control Conference
日期:2019-07-01
被引量:2
标识
DOI:10.23919/chicc.2019.8866128
摘要
Reasonable optimal path planning is one of the core requirements of autonomous vehicles. Ant colony optimization is the most famous bionic optimization method which has been widely used in path planning. However, it has some drawbacks such as slow convergence speed and ease of falling into the local optimal solution. An enhanced ant colony optimization algorithm that adopts the new inspiration function and pheromone updating strategy is provided in this paper, which aims to improve the convergence speed and search ability. In addition, our ant colony algorithm integrates the non-uniform rational B-spline curve to smooth the path. The simulation experiments indicate that this algorithm is feasible and efficient in common scene and maze scenario. Compared with the traditional ant colony algorithm, our algorithm has shorter path length and fewer iterations to converge to the optimal path.
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