Research On Path Planning Of Palletizing Robot Manipulator Based On Biogeography-based Algorithm

At present,as science and technology develop,intelligent robots and related technologies have been greatly improved.Palletizing robot is a more and more robot in the production and life of people.A higher control requirement is put forward for the movement of Palletizing robot manipulator,which requires it to be independent of dynamic obstacle avoidance and path planning.The working environment of Palletizing robot manipulator has the characteristics of variability and complexity,which decides the path planning problem of palletizing robot.As a very important research direction in the robot manipulator Motion research,the path planning it refers to the palletizing robot manipulator according to a certain performance index(such as time,distance and energy,etc.)need a collision from the starting point to the target location of the best motion-free path,and require the shortest path and the more safe choice.The Biogeography-based Optimization(BBO)algorithm is a stochastic,iterative and evolutionary process based on the natural species migration,and is a very effective algorithm in the field of path planning research.Based on this,this paper uses Biogeography-based Optimization algorithm to study the path planning of palletizing robot manipulator,and we have completed the following work:Firstly,the key technology of robot manipulator movement is introduced,including navigation,positioning and multi-sensor information fusion technology.The related definition of robot path planning and the classification of path planning are expounded.In addition,this paper introduces the methods of Robot path planning,which are the traditional methods and the new methods in recent years.Then,The actual operation flow of the BBO algorithm is introduced in detail,which is mainly two important operations of the BBO algorithm: migration operation and mutation operation.The paper also introduces the optimization process of the BBO algorithm,validates the performance of the BBO algorithm with 14 datum functions,and compares with GA algorithm and PSO algorithm,the results show that the BBO algorithm has more excellent performance,and the optimization ability is better than the traditional GA algorithm and PSO algorithm.Finally,a map model of the manipulator of Palletizing robot is established with grids.And using the method of raster serial number to generate the initial population of the Biogeography-based Optimization algorithm by using the coding and the discontinuous barrier path;then,selecting the appropriate fitness function,the function takes the path length and path security into consideration.Migration operation and mutation operationb are carried.Finally,in the static environment,the robot manipulator's global path planning,and MATLAB simulation to get the optimal path,and compared with Genetic Algorithm(GA)and artificial potential field method.The experimental results show that the path planning effect of the palletizing robot optimized by BBO algorithm is better than the traditional GA algorithm and the artificial potential field method.This study is to improve the robot manipulator Path planning.The BBO optimization algorithm is a new and good choice for traditional path planning algorithm which can not meet the ideal requirement in security and reliability.