Research On Manipulator Trajectory Planning Based On Spark Platform And Multi-Objective Artificial Bee Colony Algorithm

Under the high-speed development of economic,a lot of human activities are gradually replaced by machinery and labors are liberated.Robot can efficiently complete production tasks in all fields,which enables people devote to more advanced activities.As one kind of robots,manipulator has been applied to many industrial activities.Trajectory is one of the main factors which influence the performance of manipulator.With the goal of reducing execution time and energy consumption,this dissertation adopts artificial bee colony(ABC)algorithm to plan manipulator trajectory.After briefly introducing the significance and methods of manipulator trajectory planning(MTP),this dissertation mainly improves the ABC algorithm to multi-objective ABC(MOABC)algorithm,which is used to optimize manipulator trajectory.The main content of the dissertation is as follows:(1)This dissertation analyzes the research status at home and abroad.Besides,it highlights MTP method and ABC algorithm.(2)This dissertation puts forward the multi-objective improvement of single-objective ABC algorithm.By modifying the calculation of solution's fitness value and the solution selection method,the algorithm can solve multi-objective optimization problem and can get results approaching Pareto front.This dissertation also parallel runs MOABC on the Spark platform to accelerate the calculation.The experimental results show that the modified MOABC algorithm can solve multi-objective problem effectively and the algorithm run faster on the Spark platform.(3)This dissertation uses the MOABC algorithm to optimize manipulator trajectory.This method calculates the points in MTP by designing the structure of solutions in MOABC algorithm.And then,plan the trajectory.It also reflects constrains to the object values to select trajectory.Besides,the dissertation modifies the optimization model to parallel run it on the Spark platform.Experiments show that the optimization model put forward in this dissertation can get continuous and smooth trajectories.The simulation of the manipulator also further validates the effectiveness of the trajectory.