基于改进蚁群算法的电动叉车路径规划技术研究

Research on the path planning technology of electric forklift truck based on improved ant colony algorithm

针对电动叉车路径快速规划问题,从启发信息、信息素更新规则和平滑策略出发,研究一种改进的蚁群算法。该算法采用人工势场法求得当前节点与目标点距离,引力函数的引用使机器人在搜索过程中有较为明确的目标点范围,从而构建的启发信息能有效提高机器人收敛速度;提出一种改进的信息素更新规则,根据最优最差蚂蚁策略使得信息素在更小的区间内变化,减缓信息素的正反馈累计过程,使蚁群较大程度地遍历所有可能最优路径,降低局部最优解产生的概率;构建三角剪枝算法,顺次取路径中三个节点,连接首尾节点,其间经历的元素集合与障碍物元素集合并集为空,则无冲突,可省略其三个节点的中间节点,以此打破传统蚁群算法八自由度搜索和步长只能为1或2的规则限制。经Matlab仿真分析,验证了文中算法的可行性和高效性。

For the fast path planning problem of electric forklift truck,an improved ant colony algorithm is studied,starting from enlightening information,pheromone updating rules and smoothing strategy.The algorithm uses the artificial potential field method to obtain the distance between the current node and the target point,The reference of the gravitational function makes the robot have a relatively clear target point range in the search process,Thus,the inspired information constructed can effectively improve the convergence speed of the robot;Introduce an improved pheromone update rule,Changes in pheromones within smaller intervals according to the optimal worst ant strategy,Slow down the positive feedback cumulative process of pheromones,Making the colony largely traverse all possible optimal paths,Reduce the probability of the local optimal solution generation;Building a triangular pruning algorithm,Three nodes in the sequential path,Connect the first and end nodes,If the set of elements experienced and the combination of obstacle elements is empty,there is no conflict,To omit the middle node of its three nodes,This breaks the rule limit of the traditional ant colony algorithm eight DOF search and step size of only 1 or 1.The feasibility and high efficiency of the present algorithm are verified by Matlab simulation analysis.