太阳能光伏板清洁机器人路径规划研究与应用

发布时间：2018-06-20 10:07

本文选题：路径规划 + 栅格法环境建模　；参考：《兰州理工大学》2017年硕士论文

【摘要】：利用移动机器人对太阳能光伏板进行清洁的首先任务是解决路径规划的问题。本文研究了在西部地区大型太阳能光伏板发电站的环境背景下,移动平台式清洁机器人基于改进蚁群算法进行全局路径规划的解决办法。在过去环境模型中只显示二维长度信息的基础上,进行拓展改进——增加危险度这一概念,更加逼近现实的模拟智能路径规划问题;并且实现对太阳能光伏板发电站三维地图信息的环境建模,最后进行全局三维路径规划问题的研究与应用。主要工作如下:(1)针对建设在西部地区大型太阳能发电站光伏板清洁难题,提出轮式移动机器人清洁的解决方案。以太阳能光伏发电站实况模拟搭建环境模型,对光伏板清洁机器人的全局路径规划问题进行了研究。将太阳能光伏板设置为环境地图中的障碍物,提出了一种基于概率理论与蚁群算法相结合的改进栅格环境建模方法,通过在搜索路径中选择经过概率加权的策略,进行全局路径规划的模拟仿真实验。实验结果证明,较传统建模方法,改进后的建模方法具有一定的优越性。(2)为了克服蚁群算法中控制参数难以确定、易陷入局部自由度、早熟等现象,采用云模型理论对蚁群算法进行改进,通过对云隶属函数的参数控制,实现算法的自适应调整策略,最终减少算法的迭代速度。与基本蚁群算法的对比实验结果证明,改进蚁群算法的光伏板清洁机器人路径规划方法提高了机器人路径规划效率,且能安全避开障碍物。(3)针对清洁机器人在工作环境中,因为气候变化和沙尘天气影响,在规划路径中出现的动态障碍物等冲突问题,希望提高机器人路径规划中的越野性能和工作效率,提出一种三维路径规划的方法。依据地势海拔的高低不同,进行概率论分布来设置不同的通过优先级,将地势海拔的高低变化和最短最优的路径相互平衡,从而智能合成一条距离最短且路径中高坡与低谷地形难度适中的路径,利用MATLAB软件设计了仿真实验环境,验证了该方法的有效性。(4)根据文中的仿真实验结果,结合实际中成熟且可高度自由定制的实验平台,进行了大量的模拟实验,获得了珍贵的实验数据,并且对此进行研究,得出对比仿真模拟实验和实际工作要求的差距,指出不足点和未来工作的重心方向。
[Abstract]:The first task of cleaning solar photovoltaic panels with mobile robots is to solve the problem of path planning. In this paper, the solution of global path planning based on improved ant colony algorithm for mobile platform cleaning robot in the environment of large solar photovoltaic power station in western region is studied. On the basis of only displaying two-dimensional length information in the environment model in the past, this paper extends the concept of improving-increasing the risk degree, and approaches the practical simulation intelligent path planning problem. The environmental modeling of three-dimensional map information of solar photovoltaic power station is realized. Finally, the global three-dimensional path planning problem is studied and applied. The main work is as follows: (1) aiming at the problem of photovoltaic panel cleaning in large solar power station in the western region, the paper puts forward a solution to the cleaning of wheeled mobile robot. The global path planning problem of photovoltaic panel cleaning robot is studied based on the environment model of solar photovoltaic power station. The solar photovoltaic panel is set as the obstacle in the environmental map. An improved grid environment modeling method based on the combination of probability theory and ant colony algorithm is proposed. The simulation experiment of global path planning is carried out. The experimental results show that compared with the traditional modeling method, the improved modeling method has some advantages. In order to overcome the difficulty of determining the control parameters in ant colony algorithm, it is easy to fall into the local degree of freedom and precocity. The ant colony algorithm is improved by using cloud model theory. By controlling the parameters of the cloud membership function, the adaptive adjustment strategy of the algorithm is realized, and the iterative speed of the algorithm is finally reduced. Compared with the basic ant colony algorithm, the experimental results show that the path planning method of photovoltaic clean robot with improved ant colony algorithm improves the efficiency of robot path planning, and can safely avoid obstacles. Because of the impact of climate change and dust weather, the dynamic obstacle in the path planning is a conflict problem. In order to improve the off-road performance and work efficiency of robot path planning, a three-dimensional path planning method is proposed. According to the elevation of the terrain, the probability distribution is carried out to set different priorities to balance the variation of elevation and the shortest and optimal path. So we can intelligently synthesize a path with the shortest distance and moderate difficulty of high slope and valley terrain in the path. The simulation experiment environment is designed by using MATLAB software, and the validity of the method is verified. (4) according to the simulation results in this paper, the simulation results are given. Combined with the mature and highly customizable experimental platform in practice, a large number of simulation experiments have been carried out, and precious experimental data have been obtained, and the gap between the simulation experiment and the actual work requirements has been drawn. Points out the shortcomings and the direction of the center of gravity of future work.
【学位授予单位】：兰州理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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