基于改进蚁群算法的导览机器人平滑路径规划

Smooth Path Planning of Navigation Robot Based on Improved Ant Colony Algorithm

为了解决传统蚁群算法在导览机器人路径规划中,存在路径拐点多、规划路径非最短,路径搜索盲目性大等不足,提出一种改进蚁群算法。首先,选用栅格地图模拟导览机器人的运行环境,采用起点、终点双向搜索的16方向24邻域搜索策略,增加搜索方向,扩大蚂蚁搜索视野,提高全局搜索能力;然后把起点、当前节点、下一节点和终点的信息加入启发函数中,增加搜索路径时的针对性;另外引入伪随机状态转移策略和动态调整的信息素挥发系数,提高收敛速度和避免算法早熟;最后采用三次B样条曲线对上述得到的路径进行平滑处理。在仿真平台上,经过与其他算法对比,验证了论文算法在不同复杂程度环境地图中的有效性和优越性。

In order to solve the shortcomings of the traditional ant colony algorithm in the path planning of navigation robot,such as many path inflection points,non-shortest planned path and great blindness of path search,an improved ant colony algorithm is proposed.Firstly,the grid map is used to simulate the running environment of the navigation robot,and the 16 direction 24 neighborhood search strategy of two-way search of starting point and ending point is adopted to increase the search direction,expand the search field of ants and improve the global search ability.Then,the information of the starting point,the current node,the next node and the end point is added to the heuristic function to increase the pertinence of searching the path.In addition,pseudo-random state transition strategy and dynamically adjusted pheromone volatilization coefficient are introduced to improve the convergence speed and avoid premature convergence of the algorithm.Finally,cubic B-spline curve is used to smooth the above path.On the simulation platform,compared with other algorithms,the effectiveness and superiority of this algorithm in different complexi ty environment maps are verified.