Abstract: In order to solve the problem of insufficient operation efficiency of a single wall climbing robot in large storage tank environment, a multi-robot task planning method is proposed. Firstly, the grid map of large storage tank environment is constructed, and several closed sub areas are divided according to the environmental characteristics. Secondly, in order to give full play to the working ability of multi-robots, the mathematical model of multi-robot task allocation is established with the goal of minimum working time. The elite strategy and mutation strategy are introduced to improve the optimization ability of the firefly algorithm. The task allocation of multiple robots is carried out by improving the firefly algorithm, and the working sub areas of each robot are obtained. By designing the priority and backtracking idea of robot motion direction, the problem of complete coverage path planning and dead zone escape in robot human sub area is solved. Based on the kinematic model of the robot, the inner and outer loop trajectory tracking controller is designed. Then, the simulation experiment environment is set up to simulate the proposed multi-wall climbing robot cooperative operation algorithm. The experimental results show that the algorithm is effective and feasible, and the improved firefly algorithm has good optimization ability.

Key words: large storage tank, multi-wall climbing robot, task allocation, firefly algorithm, complete coverage path planning, trajectory tracking

摘要： 为解决单一爬壁机器人在大型储罐环境中作业效率不足的问题，提出了一种多机器人任务规划方法。构建了大型储罐环境的栅格地图，依据环境特点划分多个封闭子区域。为充分发挥多机器人的作业能力，以作业时间最少为目标建立多机器人任务分配的数学模型；引入精英策略和突变策略来提高萤火虫算法的寻优能力，通过改进萤火虫算法进行多机器人任务分配得到各机器人工作子区域。通过设计机器人运动方向的优先级及回溯思想解决机器人子区域内部的遍历路径规划及死区逃离问题。基于机器人的运动学模型设计了内外环轨迹跟踪控制器。设置仿真实验环境对所提出的多爬壁机器人协同作业算法进行仿真实验，实验结果表明该算法的有效性和可行性，且改进的萤火虫算法具有较好的寻优能力。

关键词: 大型储罐, 多爬壁机器人, 任务分配, 萤火虫算法, 全覆盖路径规划, 轨迹跟踪