Research On Autonomous Obstacle Avoidance Planning Based On ROS Robot

With the large number of applications of robots,the intelligentization of mobile robots has also become a hotspot of people 's attention.People began to pay attention to how to realize the robot to avoid obstacles in an unknown environment,and plan a safe and collision-free path with a short distance to reach the destination smoothly.This has also become an important problem that needs to be solved to realize the intelligentization of mobile robots.Although research on path planning has also made some progress,there are still problems such as low path planning efficiency,nonoptimal path,and poor dynamic obstacle avoidance performance.In the early research of mobile robots,many standards are not uniform,the reuse rate of robot codes is low,and unnecessary research and development work is added.Modular,standardized,and systematic development standards have become an inevitable choice for robot research.The emergence of the operating system Robot Operating System(abbreviated as ROS)has just successfully solved this problem.With the advantages of supporting multiple languages and high reliability,it has attracted the attention of researchers.Research on autonomous obstacle avoidance planning of mobile robots based on ROS system,the main research contents is as follows:First,this paper studies the ant colony algorithm with better global path planning performance.Aiming at the shortcomings of the slow convergence speed of the traditional ant colony algorithm,a new initial pheromone setting model is established to solve the lack of initial pheromone concentration in the ant colony algorithm,reducing the blindness of algorithm optimization,so that the algorithm can converge in a shorter time and improve Convergence speed,thereby reducing the execution time,using simulation software to test the optimized algorithm shows that the algorithm's path planning performance has improved.Secondly,this paper studies the local path planning of the robot.Select the more mature dynamic window method used in ROS as the local path planning algorithm,first briefly introduce the principle of the algorithm,because the dynamic window algorithm has the problems of lack of target point guidance and prone to oscillation,this article on the conflict judgment value and evaluation The weights of each factor in the function are set reasonably to avoid the robot from oscillating or stagnation through the narrow channel.At the same time,drawing on the idea of layered algorithm,the ant colony algorithm and the Dynamic Window Approach(DWA)are mixed and used,and the global path is used as the initial path of the robot to make it track the movement.If it is detected that there is an obstruction on the robot's movement route,the local target point is added according to the current position of the robot.Under the guidance of the target point,the blindness of the algorithm is reduced,and the overall path planning is better,so as to achieve better dynamic obstacle avoidance and Planning effect.From the analysis of the simulation experiment results,it can be seen that the algorithm given in this paper can make it pass through narrow areas and have better obstacle avoidance effect on dynamic obstacles.Finally,this paper sets up three experimental scenarios of global path planning,dynamic obstacle avoidance,and crossing narrow passages.With the help of an intelligent mobile experiment platform,the path planning performance after algorithm optimization is tested separately.Experiments verify that mobile robots have good autonomous obstacle avoidance planning capabilities in static and dynamic environments.