Design And Application Of Mobile Robot Navigation System Based On Swarm Intelligence Algorithm

In recent years,with the rapid development of artificial intelligence,electronic,computer,embedded processor and mechanical and other disciplines,the mobile robot has gained widespread attention in the market.The key technology of mobile robot is the research of path planning algorithm.However,most of the traditional path planning algorithms are inadequate,so the search for the optimal algorithm has become a hot research topic.The characteristics of ant colony algorithm optimization effect based on the traditional ant colony algorithm is improved,and the performance of the improved ant colony algorithm are compared by simulation,respectively,in the static environment and dynamic obstacle environment simulation,the improved ant colony algorithm is applied to mobile robot navigation platform,implementation the ROS of mobile robot self localization and navigation function based on.First,in order to solve the obstacle collision problem in static environment,this paper presents an improved ant colony algorithm(QACS)based on global path planning algorithm,and through a large number of simulation experiments verify the feasibility.In order to overcome the traditional ant colony algorithm and the diversity of the population is low,the slow convergence problem by introducing the quantum operator,quantum state vector to increase population diversity and convergence speed while introducing quantum rotation gate to control algorithm,to avoid premature convergence.In order to verify the excellent algorithm,modeling of the static environment,the ant colony algorithm through the establishment of different environment map and set different parameters for the improvement of a large number of simulation experiments,the experimental results show that the improved algorithm can find the global optimal or suboptimal solution,and has faster convergence speed.Secondly,according to the path planning problem of mobile robot in the dynamic complex environment,a new algorithm based on improved ant colony algorithm is proposed,which combines the global path planning with the local path planning based on the rolling window.In the local rolling collision avoidance planning prediction for dynamic obstacle direction uncertainty,propose two prediction schemes,and gives the corresponding collision avoidance strategy.Then in the static environment,add the dynamic obstacles to determine the direction of dynamic obstacle and uniform motion simulation,the simulation experiment shows that the proposed algorithm is effective to solve the problem of path planning of mobile robot in dynamic environment.Thirdly,the navigation system based on ROS robot is built.This paper mainly introduces the hardware and various parameters of the TurtleBot robot and the design of the software frame,mainly introduces the Navigation function package in the robot operating system(ROS).In the realization of navigation and positioning functions,the paper focuses on the functions of the package and node used in the navigation process: AMCL method and the cost map environment modeling method.Through the experiment of map building and navigation test,the test of the mobile robot in the actual environment is carried out,which shows the feasibility of the improved algorithm.Finally,the application of ROS based mobile robot in intelligent transportation system.First of all,to solve the problem of parking difficulty and low utilization rate of parking space,the concept of unattended parking service system is put forward.Next will APP Application module,the parking management module,the navigation robot module three big modules to solve the parking problem of low utilization ratio.Finally,through the navigation experiments in the garage,it is proved that the mobile robot can lead the car owners to reach the designated parking spaces,to solve the problem of parking is difficult,and truly realize the status of the garage...