Abstract: To solve the problems of low efficiency, not to consider collision and poor applicability of the current robot path planning method for spraying entities with complex structure, a discrete grey wolf optimizer algorithm for solving multilayer decision problems was proposed and applied to the above path planning problem. In order to transfer the grey wolf optimizer algorithm with continuous domain to discrete grey wolf optimizer algorithm for solving multilayer decision problems, the matrix coding method was used to solve the coding problem of multilayer decision problem, a hybrid initialization method based on prior knowledge and random selection was proposed to improve the solving efficiency and precision of the algorithm, the crossover operator and the two-level mutation operator were used to define the population update strategy of the discrete grey wolf optimizer algorithm. In addition, the path planning problem of spraying robot was simplified to the generalized traveling salesman problem by the graph theory, and the shortest path model and path collision model of this problem were established. In the path planning experiment, compared with particle swarm optimization algorithm, genetic algorithm and ant colony optimization algorithm, the proposed algorithm has the average planned path length decreased by 5.0%, 5.5% and 6.6%, has the collision time reduced to 0, and has smoother paths. Experimental results show that the proposed algorithm can effectively improve the spraying efficiency of spraying robot as well as the safety and applicability of the spraying path.

Key words: spraying robot, path planning, generalized traveling salesman problem, multilayer decision, grey wolf optimizer algorithm

摘要： 针对目前用于复杂结构实体喷涂的机器人路径规划方法存在的效率低、未考虑碰撞以及适用性差等问题，提出一种用于求解多层决策问题的离散灰狼算法，并把该算法用于该路径规划问题的求解。为了将连续域灰狼算法改为用于求解多层决策问题的离散灰狼算法，采用矩阵编码方法解决多层决策问题的编码问题，提出基于先验知识与随机选择的混合初始化方法提高算法求解效率和精度，运用交叉算子与两级变异算子定义离散域灰狼算法的种群更新策略。另外，运用图论将喷涂机器人路径规划问题简化为广义旅行商问题，并建立了该问题的最短路径模型和路径碰撞模型。在路径规划实验中，相较于粒子群算法、遗传算法和蚁群算法，提出的算法规划的平均路径长度分别减小了5.0%、5.5%和6.6%，碰撞次数降低为0，且路径更平滑。实验结果表明，提出的算法能够有效提高喷涂机器人的喷涂效率，以及喷涂路径的安全性和适用性。

关键词: 喷涂机器人, 路径规划, 广义旅行商问题, 多层决策, 灰狼算法