三臂凿岩机器人孔序规划及其优化

Sequence planning of three-boom tunnel-drilling robot and optimizing

智能化是工程装备转型升级方向之一,以中间钻臂独有的工作空间为协调区间,将三臂凿岩机器人孔序规划问题化为涉及干涉的3-TSP问题,改进蚁群优化(ACO)算法平衡各钻臂钻孔时间,优化分配各钻臂钻孔任务,采用n/4动态候选列表的方法,加速算法收敛并获得更优解,同时去除每一次迭代最优路径中的相交路径,开发图形界面软件并嵌入算法。仿真结果显示整体效率提高35%。

Intelligence is one of the upgrading direction of engineering equipment. Taking the workspace of the middle boom as the collaborative workspace and converting the drilling sequence into three-traveling salesman problem( TSP) which involving interference between booms,improve ant colony optimization( ACO) algorithm to balance the time of drilling between booms. Meanwhile,optimizing distribution drill task of each boom,n/4 dynamic candidate list method is adopted to accelerate algorithm convergence and gain optimal solution. Remove the intersections in optimal paths of every iteration,develop graphical interface software and embed algorithm.Simulation result shows it can increase efficiency by 35 %.