Intelligent Vehicle Test Platform Construction And Obstacle Avoidance Algorithm Research

With the continuous development of smart car technology,the application of smart cars is involved in various scenarios of society.The navigation and obstacle avoidance of intelligent vehicles are the primary prerequisite for their unmanned work,and one of the basic functions that reflect their intelligence.Therefore,the research on how to achieve autonomous navigation and obstacle avoidance by the sensors carried by intelligent vehicles in the environment they are driving in has gradually attracted a large number of researchers.In this paper,on the basis of sufficient literature research,a Songling robot wire control chassis was selected,a PC was configured as the upper computer of the intelligent vehicle,a ROS platform was installed as the main control system,a Sprint 16-line LIDAR was installed as the environmental sensor,a scenario-specific test site was established,different kinds and locations of obstacles were placed,and an experimental environment and test platform were formed.Based on ROS robot operating system and experimental environment,the experimental scene map is constructed by LIDAR scanning;global path planning for intelligent vehicles based on A* algorithm;local obstacle avoidance strategy based on DWA dynamic window method fused with A* algorithm for intelligent vehicles.Continuous simulation optimization is performed in the simulation.Then the optimized program and parameters are written as ROS algorithm plug-in for the built intelligent vehicle,and finally the navigation and obstacle avoidance tasks of the intelligent vehicle are completed.The following work was mainly carried out.Firstly,this paper reviews the research status and navigation and obstacle avoidance methods of intelligent vehicles at home and abroad.In order to study the navigation and obstacle avoidance algorithms of intelligent vehicles,the hardware part and software part of the intelligent vehicle test platform are built based on ros robot operating system.The construction of the intelligent vehicle test platform is completed.Secondly,the intelligent vehicle navigation and obstacle avoidance is divided into global path planning and local obstacle avoidance planning.The A* algorithm is also studied and its feasibility for global path planning of intelligent vehicles is simulated using MATLAB.In terms of local obstacle avoidance,the DWA dynamic window method is studied and the A* algorithm is fused with the dynamic window method for the local obstacle avoidance algorithm of intelligent vehicles.The feasibility of the proposed fusion algorithm for navigation and obstacle avoidance in different environments is verified using MATLAB.Finally,in order to verify the performance of the A* global path planning algorithm and the proposed fusion obstacle avoidance algorithm in the navigation and obstacle avoidance of the intelligent vehicle built in this paper,an experimental site is arranged and the intelligent vehicle built in this paper and the global path planning algorithm used and the proposed fusion obstacle avoidance algorithm are experimented in a real vehicle.The experimental results show that the proposed fusion obstacle avoidance algorithm and A*global path planning algorithm can make the intelligent vehicle achieve navigation and obstacle avoidance,and have good practicality.