Research On Path Planning And Motion Control Of Mobile Robots

In the field of intelligent mobile robots,the path planning problem is a key issue that limits its development.How to plan a non-collision route to make it safe to reach the target point is the focus of current research.Based on the ROS operating system,this paper uses the depth camera Xtion PRO LIVE and the laser radar RPLIDAR A2 to study the path planning problem on the TurtleBot2 mobile robot.Based on the current algorithm,a hybrid algorithm is proposed and analyzed through experiments.verification.The main research content is as follows:(1)In this paper,we use RGB-D depth camera and laser radar to build a robot environment awareness system.We introduce in detail the relevant hardware systems,including the depth camera Xtion PRO LIVE,laser radar RPLIDAR A2,ROS and Gazebo simulation software,and in the construction The principle of Fastslam2.0 algorithm is elaborated in detail,and the AMCL algorithm is introduced in the aspect of positioning.(2)Using Fastslam2.0 algorithm,through experimental research,the influence of two variables,number of particles and change time,on the establishment of maps was analyzed;using a robot equipped with Xtion PRO LIVE,based on the map created by Lidar,The feasibility of the AMCL algorithm.(3)It mainly introduces the path planning of robots.The content of the global algorithm is mainly introduced for A* algorithm and RRT algorithm and the simulation analysis is performed.The algorithm to be adopted is selected according to the simulation results.In the local planning,the artificial potential field method is mainly used to optimize the traditional artificial potential field method.,Improvement and simulation experiments,the experimental results show that the improved algorithm can solve the problems existing in traditional algorithms.Finally,a hybrid algorithm of two algorithms is proposed in combination with A*algorithm and improved artificial potential field method.(4)The motion control of the differential robot is introduced,and the robot's autonomous positioning and path planning experiments are performed.The experiment was implemented using the mixed algorithm of A* algorithm and improved artificial potential field method.In the experiment process,the video was taken and the experimental data was analyzed.The experimental results showed that the hybrid algorithm was feasible.