Research On Mapping And Navigation Technology Of Mobile Robot Based On ROS

In recent years,mobile robots have been widely used in various fields,and the related technologies have made a great upsurge in the field of robotics both at home and abroad.In order to realize autonomous navigation,the understanding and localization of environment is an important sign and characteristic of intelligent mobile robot.Real time localization and map building(SLAM)in unknown environments has been a hot research topic in the field of mobile robot technology.This project for the indoor service robot system,carry out the relevant research and technology mapping and navigation of mobile robot based on ROS,including the ROS mobile robot operating system development,indoor environment map construction,independent exploration and local path planning based on the specific research contents are as follows.First of all,we design the hardware structure of mobile robot,and complete the hardware system of robot sensors.In the software control system,modular design,based on distributed computing,the development of mobile robot based on ROS system platform,the mobile robot sensor data acquisition,mobile control,mapping,navigation and environment observation nodes were designed,finally build a complete set of mapping navigation robot system.The robot is capable of real-time mapping and navigation,and has good human-computer interaction ability.Secondly,in view of the large computational complexity of the state estimation unscented Calman filter(UKF)algorithm in SLAM systems,a UKF estimation algorithm based on local sampling is proposed.According to the characteristics of the state vector in the algorithm,the sampling strategy is only used to sample some of the current state estimation data in the UT sampling of the UKF algorithm,which reduces the computational complexity of the state estimation.The new sampling algorithm is deduced and analyzed.The simulation results show that the proposed algorithm can reduce the computational complexity in the case of ensure the filtering positioning accuracy and improve the real-time performance of the robot.We propose an improved dynamic window(DWA)local path planning algorithm based on global path.First carries on the analysis and simulation experiment research of the formula for the traditional DWA algorithm,the evaluation function in the presence of non essential items and special environment navigation problems,DWA algorithm is proposed based on global path planning,and demonstrate the effectiveness and robustness of the improved method by MATLAB simulation analysis.Finally,we use the SLAM mobile autonomous exploration robot experimental platform for robot experiments,to verify the part of UKF localization algorithm based on sampling and the feasibility of the improved DWA local path planning algorithm.