Research On Intelligent Path Planning Of Tower Crane

Under the background of the Internet and intelligent manufacturing,hoisting machinery enterprises are transforming into digital ones.As the most widely used mechanical equipment in the construction industry,tower crane is more intelligent,which is the general trend of future development.As a key part of crane intelligence,intelligent path planning plays an important role in the development of cranes.In this paper,the intelligent path planning problem of tower crane in three-dimensional environment is studied.The path planning algorithms commonly used by scholars at home and abroad are summarized.Combined with the operation characteristics of tower crane in building environment,the artificial fish swarm intelligent algorithm is used to study the static environment,dynamic environment and complex unknown environment respectively.The specific research contents are as follows:Firstly,aiming at the problems of many inflection points and large load swing caused by the traditional manual control tower crane for transporting goods,a three-dimensional map environment model was established to simulate the building environment,and the traditional artificial fish swarm algorithm was improved.The adaptive moving step size related to the next position and the foraging behavior based on the optimal artificial fish and the nearest artificial fish are introduced,and the survival competition mechanism is used to prevent the artificial fish from degradation,which improves the optimization ability of the algorithm to a certain extent.A smooth obstacle avoidance path suitable for tower crane is obtained by introducing the redundant node screening rule and using cubic spline data interpolation to fit the curve.The simulation results show that the improved algorithm can find a better obstacle avoidance path for the tower crane in the static environment and improve the safety and efficiency of the tower crane.Secondly,in view of the difficulty of obstacle avoidance path planning for tower cranes in dynamic environment,a dynamic obstacle avoidance strategy is proposed.The initial path in the static environment is used as the path buffer area.When an obstacle appears on the initial path,the invalid path that may collide is deleted and local path planning is performed to correct the crane operation path.The artificial fish extinction mechanism and disturbance mechanism are added to the algorithm,and the error of adjacent iterative solutions is used as the iteration termination criterion,which shortens the time of local path planning of crane.The simulation results prove the feasibility of the improved intelligent path planning method in three-dimensional dynamic environment.Finally,aiming at the problem that the tower crane works in a complex unknown environment,the sensor cannot obtain the complete map information in the first time,the rolling window method is introduced into the path planning method.The three-dimensional cylindrical field of view that conforms to the working characteristics of the tower crane is set to ensure the integrity of the obstacle information in the field of view,and the local sub-target points are determined in the field of view.The random chaotic sequence generated by the Tent chaotic map is used to improve the initial population of the artificial fish swarm algorithm and improve the quality of the initial solution.The global optimal path is divided into multiple local paths,so that the crane gradually reaches the end point through each local path.The simulation results prove the applicability of the scheme.