Research On Environmental Modeling And Path Planning Of Mobile Robots

In recent years,artificial intelligence technology has attracted great attention,and the field of mobile robots has gradually become a hotspot in the world.Mobile robots integrate computer,automatic control,mechanism,and cybernetics expertise,and become one of the active areas of artificial intelligence.It is one of the more active areas in the development of artificial intelligence.Among them,path planning and trajectory tracking are the core technologies in the decision-making and control of mobile robots.How to efficiently plan an optimal and safe path for mobile robots and achieve accurate control has always been a challenging research direction.Firstly,by analyzing the environment modeling method of mobile robot,the grid modeling method is selected to model the space environment.A map model of a room in a mechanical building under real environment is established by using lidar and Clearpath ROS robot.The map is processed in MATLAB,and the raster map model is finally obtained.Secondly,the basic principle and searching process of path planning of A* algorithm are discussed.The number of searching directions is increased by implementing extended neighborhood searching strategy of A* algorithm.The path generated by A* algorithm is processed by curve fitting to make the path smoother and safer.The path planning results,length and time are considered separately.The traditional A* algorithm and the improved A* algorithm are compared and analyzed through the simulation experiment with MATLAB software.The simulation results show that the improved A* algorithm has better planning effect.Then,the basic principle of classical ant colony algorithm is elaborated,and three important parameters affecting the performance of ant colony algorithm are discussed and analyzed in depth.The relationship curve between the selection of parameters and the performance of the algorithm is obtained by simulation in MATLAB.Under the optimal combination of parameters,the traditional ant colony algorithm is improved by dynamic adaptive adjustment strategy,and the efficient path based on ant colony algorithm is realizedFinally,the kinematics model and trajectory tracking model of wheeled mobile robot are established.The basic principle and characteristics of the model predictive control algorithm are discussed.Based on the idea of model predictive control,the linear timevarying model predictive trajectory tracking control algorithm is adopted.The trajectory tracking simulation experiments of two different paths are carried out by using MATLAB software.The results show that the control algorithm adopted can be fast and stable.It converges locally to the reference trajectory.