桥式起重机吊装系统路径规划研究

发布时间：2018-03-15 18:14

本文选题：桥式起重机　切入点：吊装路径规划　出处：《太原科技大学》2017年硕士论文　论文类型：学位论文

【摘要】：近年来,随着各个行业的自动化、智能化水平不断提高所带来的便利与高效的驱动,大型工程机械也在向此方向发展。而智能路径规划作为一个重要的研究方向,在机器人领域已经比较成熟且得到广泛应用,但在大型工程机械如起重机方面研究相对较少。因此,本文针对桥式起重机的特点和目前研究文献中存在的不足,融合栅格法、蚁群算法,并将粒子群算法应用于动态环境中,提出了在静态和动态环境下的桥式起重机吊装路径规划方法,主要内容如下:首先,针对智能桥式起重机系统,提出基于改进的蚁群算法的吊装路径规划方法。研究在障碍物已知的静态环境中,忽略桥式起重机的吊钩升降,将其环境简化为二维栅格模型,对蚁群算法的启发函数、挥发系数等进行改进,且考虑到桥式起重机的运行特点,为避免大小车频繁制动,将原有的斜线路径改为直线,并引入代价函数来评价仿真的效果。仿真结果表明算法的可行性。其次,建立静态且环境已知的桥式起重机三维作业环境模型,利用栅格法划分空间,将桥式起重机所吊重物最大摆动距离与其安全通过障碍物的距离之和设为安全距离,将蚁群算法的启发函数、挥发系数以及适应度函数等进行改进并应用于桥式起重机三维环境的吊装路径规划。在MATLAB中进行仿真研究,结果证明了方案的可行性与有效性。最后,针对动态变化的吊装环境,提出在动态环境中的桥式起重机吊装路径规划。仍由栅格法建模,通过将优先选择的思想、敏感粒子根据适应度值改变来探测环境并根据阈值触发响应机制、及对动态粒子群算法的适应度值的改变,来进行规划。为避免大小车频繁制动,仍采用直线路径。仿真结果表明此方法不仅可用于动态环境且效果有保障,安全性高。
[Abstract]:In recent years, with the automation of various industries, intelligent level of continuous improvement of the convenience and efficiency of driving, large-scale construction machinery is also in this direction, and intelligent path planning as an important research direction, It has been mature and widely used in the field of robot, but the research on large-scale construction machinery such as cranes is relatively few. Therefore, in view of the characteristics of bridge cranes and the shortcomings of the present research literature, the fusion grid method is used in this paper. Ant colony algorithm and particle swarm optimization (PSO) algorithm are applied to dynamic environment. A method of crane hoisting path planning in static and dynamic environment is proposed. The main contents are as follows: firstly, aiming at intelligent bridge crane system, A method of hoisting path planning based on improved ant colony algorithm is proposed. In the static environment with known obstacles, the lifting hooks of bridge cranes are ignored, and their environment is simplified as a two-dimensional grid model, which is a heuristic function for ant colony algorithm. The volatilization coefficient is improved, and considering the operation characteristics of the bridge crane, in order to avoid frequent braking of the trolley, the original diagonal path is changed into a straight line. The cost function is introduced to evaluate the simulation effect. The simulation results show that the algorithm is feasible. Secondly, a static and known three-dimensional operating environment model of bridge crane is established, and the space is divided by grid method. In this paper, the sum of the maximum swing distance and the distance between the weight hoisted by the bridge crane and the distance from which the crane can safely pass through the obstacle is set as the safe distance, and the heuristic function of the ant colony algorithm is put forward. The volatilization coefficient and fitness function are improved and applied to the hoisting path planning of bridge crane in 3D environment. The simulation results in MATLAB show that the scheme is feasible and effective. In view of the dynamic changing hoisting environment, the hoisting path planning of bridge crane in dynamic environment is put forward. The sensitive particle detects the environment according to the change of fitness value, triggers the response mechanism according to the threshold, and changes the fitness value of the dynamic particle swarm optimization algorithm. The simulation results show that this method not only can be used in dynamic environment, but also has high security.
【学位授予单位】：太原科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TH215;TP18

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