Research On Obstacle Avoidance And Path Planning For Mobile Robots Based On Optimized Hybrid Ant Colony Algorithm

The generation of robots is a symbol of the progress of the times and the ability to enable robots to autonomous navigate in a human environment is a prerequisite for mobile robot applications.However,due to the complex indoor environment,achieving autonomous navigation under this environment requires not only the planning of optimal paths but also avoiding obstacles safely.Therefore,the study of path planning and obstacle avoidance becomes very important.The main work of this paper is as follows:Firstly,the research status of mobile robot navigation technology,path planning and obstacle avoidance technology are researched.ROS is selected as the robot operating system and laser sensor is used to obtain environmental information.The overall scheme design of path planning and obstacle avoidance of mobile robot based on ROS is completed.Secondly,aiming at the problem that the random search of ant colony algorithm is inefficient and easy to fall into the local optimum at the initial time,a new hybrid optimization ant colony optimization algorithm is proposed.The algorithm combined with the target gravitation generated by the artificial potential field to construct the heuristic factor,then combines the heuristic factor and the initial heuristic factor of the ant colony algorithm to construct the comprehensive heuristic information.The search speed is improved and search time is reduced.The pheromone of the ant colony algorithm is improved by using the principle of the wolf colony algorithm to avoid falling into the local optimum.Finally,using the path optimization algorithm to improve the planning path,which makes the path inflection points are reduced,and the path applicability is increased.Thirdly,a method to predict obstacle avoidance is proposed in this paper.The method first uses the laser sensor to obtain the obstacle data,and then processes the laser sensor detection data and builds the obstacle model,and finally invokes the predictive obstacle avoidance algorithm to predict whether the obstacle will collide with the robot.This method allows the robot to react in advance to dynamic obstacles that will collide with it,increasing the success rate of obstacle avoidance.Then use the optimized hybrid ant colony algorithm to find the global path,use the predictive obstacle avoidance method to perform partial obstacle avoidance,compare coordinates to detect dynamic obstacles,and call the partial obstacle avoidance algorithm during robot advancement to realize the dynamic path planning of the robot.Finally,the ROS2-bot robot was used as the experimental platform.Use ROS operating system to invoke global path planning and partial obstacle avoidance algorithms.Experiments in different scenarios show that the algorithm has high reliability and adaptability.