Research On SLAM And Path Planning Of Indoor Mobile Robot

With the rapid development of science and technology,mobile robots are closely related to human life and play an important role in many fields.In the mobile robot system,map construction,positioning and path planning methods are the main problems to be solved.In this paper,a wheeled differential mobile robot equipped with lidar sensor is designed for indoor application scenarios.An adaptive particle number SLAM algorithm and an improved ant colony algorithm are proposed to improve the autonomous obstacle avoidance ability of mobile robots in indoor environment.The specific research contents are as follows.:(1)The system structure of the wheeled differential mobile robot is designed,the communication framework of the mobile robot system is built,and the kinematics model,track model and lidar model of the wheeled differential mobile robot are established.Aiming at the problems of low map accuracy,poor particle diversity and excessive calculation of traditional RBPF algorithm,an improved RBPF method is proposed.Simulation experiments show that the improved SLAM algorithm improves the positioning and mapping accuracy of the robot in the indoor environment and accelerates the convergence speed of the algorithm.(2)Aiming at the problem that ant colony algorithm is easy to fall into local optimum and slow convergence speed,an improved ant colony algorithm is proposed.The coordinates of the starting point and the target point are introduced into the heuristic function to make the ant ’s path search purposeful.In the early stage of the algorithm,the pheromone concentration is unevenly distributed to speed up the search speed of the optimal path.Improve pheromone concentration update rules to reduce the probability of ants falling into local optimum.In the dynamic environment,the DWA algorithm is called for local path planning.The angular velocity scoring item is introduced into the evaluation function of the dynamic window method to enhance the ability of the mobile robot to avoid dynamic obstacles.The adaptive weight coefficient makes the robot pay attention to the fast arrival ability in the early stage of the algorithm,and the algorithm focuses on searching the optimal path in the later stage.The improved ant colony algorithm and the improved DWA algorithm are fused.The effectiveness of the fusion algorithm is verified by simulation experiments,and the autonomous navigation and dynamic obstacle avoidance of indoor mobile robots are realized.(3)Based on the ROS robot operating system,a wheeled differential mobile robot experimental platform is built.The wheeled differential mobile robot is used for experiments in three environments : indoor no obstacle,indoor static obstacle and indoor dynamic obstacle.The improved SLAM algorithm is used to construct the map of the real scene,and the obstacle avoidance experiment is carried out on the constructed map.The experimental results verify that the mobile robot can autonomously avoid obstacles to reach the target point.