Research On AGV Navigation And Control Technology Based On RBPF SLAM Algorithm

As an important branch of mobile robot,AGV is widely used in manufacturing,warehousing,logistics,port,wharf,food,chemical and other industries with its advantages of flexibility,convenient maintenance and strong extensibility.It is one of the key equipment to realize intelligent manufacturing.SLAM means that the AGV obtains surrounding environment information through sensors in an unfamiliar environment,completes its own real-time positioning and environment map construction,and realizes autonomous navigation.SLAM has become a hot and difficult topic in the research and application of AGV technology.In this paper,SLAM algorithm and path planning algorithm were studied,and an experimental platform of the AGV was built independently,and the functions of map construction,positioning and autonomous navigation of the AGV were realized by the use of laser radar,odometer and IMU sensor.The main research contents and results are as follows:Firstly,the raster map was selected as the map expression mode through analyzing commonly used SLAM map models.Being aimed at conventional RBPF SLAM algorithms' shortcomings that the positioning and map construction accuracy were lower due to particle dissipation,an improved RBPF SLAM were realized by use of integrating the most recent l laser radar observations into the proposed distribution and introducing adaptive resampling algorithm.Then,the traditional RBPF SLAM algorithm and its improved were simulated in MATLAB software,the results verified that the map constructed by improved algorithm has no disturbance,its structural features is clear and the precision is higher.Secondly,the AMCL algorithm was used to study the AGV positioning,in order to overcome the “robot kidnapping” problem faced by AGV,the accurate position and pose were reacquired by introducing random particles.The global path planning algorithm Dijkstra algorithm and A* algorithm were analyzed and simulated by MATLAB,and A*algorithm is selected as the global path planning algorithm.Furthermore,the local path planning algorithm DWA algorithm was simulated and analyzed by MATLAB,and the sampling speed range of the AGV was determined,so that AGV's real-time path planning could be realized.Then,an experimental prototype of AGV was built independently,and its motion mode was provided.In the ROS system,the laser radar and IMU were tested,and the software systems such as AGV motion control and sensor data publishing under speed mode are designed,which provides a basis for experimental research on AGV SLAM and autonomous navigation in real environment.Finally,the AGV model was created in the ROS environment,and the SLAM process and autonomous navigation simulation experiments were completed in Gazebo.The simulation results verified the feasibility of the map construction and autonomous navigation by use of improved RBPF SLAM algorithm and A* algorithm + DWA algorithm respectively.On this basis,the real experiments was successfully done on the AGV porotype.The results showed that the map construction accuracy of the improved RBPF SLAM algorithm is significantly improved,and the path planning based on A* algorithm+ DWA algorithm has achieved a more accurate autonomous navigation effect.