Research On Autonomous Navigation Technology Of Home Mobile Service Robot Based On ROS

With the integration and development of artificial intelligence,Internet of Things,and robotics in recent years,the scale of the home mobile service robot market has continued to expand.How to make robots build accurate maps and realize autonomous navigation in complex indoor environments has become a research hotspot.This topic takes home mobile service robots as the research object and focuses on the study of simultaneous localization and mapping technology and path planning algorithms in autonomous navigation systems.First,the research status of home mobile service robots and autonomous navigation technologies at home and abroad are analyzed and compared.On this basis,a crawler mobile robot platform with differential drive and PID control is built.Its hardware is based on the Raspberry Pi3B+ control board.It is the main controller and is equipped with lidar and IMU sensors for data collection.The software uses the ROS robot operating system as the software development framework for system program development.Secondly,the real-time positioning and map construction technology in the autonomous navigation system of mobile service robots are studied.During the analysis of the principle of the SLAM algorithm based on Rao-Blackwellized particle filter,it is found that the traditional RBPFSLAM algorithm is used for environmental map construction.As the algorithm iterates many times,the particle diversity will be reduced,which will cause the final map accuracy to be low.In this regard,an improved RBPF-SLAM algorithm based on dynamic adaptive ant colony optimization resampling is proposed,and the Tim Bailey simulator is used to analyze the algorithm.For verification,the accuracy of mapping has been greatly improved compared with the results of the improved algorithm.Then,the main research is to solve the path planning problem in the robot autonomous navigation system.Research the related principles of the traditional A* global path planning algorithm and the DWA local path planning algorithm.During the research process,it is found that when the traditional DWA algorithm is used for local path planning,if the robot encounters a "U" or "T"-shaped obstacles have the problem of making the robot fall into a local optimum and cannot leave.Therefore,the hybrid path planning scheme that combines the A* algorithm and the improved DWA algorithm is selected in the project.Through simulation experiment analysis,the improved hybrid path planning scheme effectively solves the problem that the robot is likely to fall into the local optimum when planning the path in a complex environment.Finally,the improved RBPF-SLAM mapping and path planning algorithms are experimentally verified by using the built mobile robot platform in the real indoor environment.At the same time,the home mobile service robot control software is designed based on the ROSMATLAB interface.This software can complete the robot Functions such as motion control and real-time image monitoring.In addition,single-point navigation,multi-point navigation and obstacle avoidance experiments were carried out on the autonomous system of the home mobile service robot proposed in this topic,which verified the practicability and effectiveness of the scheme,and achieved the expected results of the topic.