Research On Path Planning Algorithm Of Mobile Robot In Dense Obstacle Environment

With the rapid development of science and technology,robots are not only widely used in the industrial field,but also shine in people's lives.This is the result of the continuous and intelligent development of robot systems.Robots will become the main force of social labor to replace people working under repeated heavy,dangerous,harsh,and outer space environments.In terms of service work,indoor service robots such as intelligent service robots and housekeeping service robots can provide necessary assistance to humans.In the hospital scenario,mobile robots can help deliver medicines,greatly improving hospital efficiency.In a smart factory,a large number of robots are used,and due to the activities of factory employees and temporary debris piled up,the factory becomes a complex scenario.In complex and dense obstacle scenarios,how to solve mobile robot path planning and real-time obstacle avoidance,It has always been a difficulty in robot navigation.This topic focuses on the key technologies such as path planning techniques and obstacle avoidance methods for mobile robots in dense obstacle scenarios.The details are as follows:(1)Design of mobile robot software system.According to the work scene,the mobile robot is selected and the kinematic model of the mobile robot is established.The URDF model of the robot is established in the ROS system visualization tool to establish the mobile robot navigation system framework.(2)Research on robot global path planning method based on ant colony algorithm.A global path planning method for robots based on improved ant colony algorithm is proposed,and an environmental grid map environment model and a mathematical model of a classic ant colony algorithm are established,and path planning simulation experiments are conducted for simple scenarios and dense obstacle scenarios,respectively;The key parameters are tested by the control variable method to find the optimal combination of parameters.To solve the problem of the classic ant colony algorithm in dense obstacle scenarios,a solution is proposed,and a comparative experiment is designed.Finally,the effectiveness of the improved algorithm is verified.(3)Research on local obstacle avoidance method based on VFH+algorithm.Aiming at the problems of VFH and VFH+series algorithms that have threshold sensitivity,no consideration of the robot speed and obstacle speed,and the left and right oscillations of the robot during operation,a self-adjusting threshold VFH+path planning algorithm is proposed,and a comparative experiment with the traditional VFH+algorithm is carried out,and The feasibility and effectiveness of the improved algorithm are verified.(4)Experimental research.Build a mobile robot software system on the experimental platform,and design experiments to verify the effectiveness of the global path planning method and local obstacle avoidance method proposed in this paper.