Mobile Robot Path Planning Based On Variable-step Ant Colony Algorithm

With the development of artificial intelligence technology,mobile robots have been widely used in a large number of occasions such as life services,military,entertainment,and industrial applications.The application and development of mobile robots are related to everyone's vital interests,and path planning technology is an important research field of mobile robots that has been widely concerned by scholars at home and abroad.Path planning technology is a prerequisite for mobile robots to complete various important tasks.At present,a large number of groups Intelligent algorithms are applied to the path planning of mobile robots.However,traditional group intelligence algorithms all have problems such as slow convergence speed and single step size.In order to better solve the path planning problem of mobile robots,group intelligence algorithms must be targeted.Make relevant improvements.The improved adaptive ant colony algorithm designed in this paper is to improve the problem that the traditional ant colony algorithm lacks sufficient robustness in path planning.Introducing a weighting factor into the state transition probability formula to improve the convergence speed of the algorithm.The pheromone is updated adaptively according to the distribution of the solution.If the volatilization coefficient is fixedly changed,although the global search ability can be improved,the convergence speed of the algorithm is reduced.Therefore,the adaptive ant colony algorithm proposes an adaptive method to change the pheromone concentration value,select the optimal step size under various step size selection mechanisms,and improve the global search capability.Compared with the traditional ant colony algorithm,the improved ant colony algorithm can find the shortest path quickly,and has better stability and convergence.The variable-step ant colony algorithm designed in this paper,by improving the adjacency matrix scheme,realizes the spanning of the mobile robot from single step to variable step,can effectively solve the single-layer and multi-layer ant colony algorithm in the mobile robot path planning.The angle is too large and too many,and the ability to adapt to complex environments is poor.The variable-step ant colony algorithm increases the range of selectable nodes.It is no longer limited to the traditional ant colony algorithm that only moves to the surrounding neighboring position.The step size ant colony algorithm can reduce the length of the crawling path of the mobile robot.Prior to the mobile robot path planning,the pheromone concentration distribution is assigned according to priority,the distribution of important grid positions increases,the edge grid node position and non-The pheromone of the optimal path passing through the position of the grid node is reduced,and the pheromone is allocated differently.The grid environment where the mobile robot is located is modeled.Based on the connection from the starting point of the mobile robot to the target point,the pheromone is attenuated in parallel on both sides.Improve the heuristic function of the traditional ant colony algorithm to optimize the heuristic function of the mobile robot from the starting point to the target point Computing solutions,increase the probability of the desired node is selected,so that the variable step size ant colony algorithm fast convergence,path planning to complete the task.The improved variable-step ant colony algorithm designed in this paper aims to solve the problems of local optimality,deadlock,and too slow convergence speed of mobile robots in path planning by adjusting the step size of mobile robots in path planning.At the same time,in order to improve the smoothness of the path planned by the mobile robot using variable-step ant colony algorithm.Improve the mobile robot state transition probability formula to increase the probability that some important nodes are selected.It is no longer the adjacent nodes in the traditional ant colony algorithm.The smooth function optimization mechanism is designed to realize the mobile robot from single step to variable step.The crossing of the mobile robot reduces the number of corners of the mobile robot,plans a gentle curve for the corner position,and introduces a smooth guide optimization function to attract the path trajectory planned by the mobile robot to approach the optimal path and shorten the path trajectory of the mobile robot.The ant colony system pheromone allocation rules are re-enacted,the effective paths of each generation are compared and sorted,and the pheromone concentration is set proportionally according to the length of the path,and the pheromone penalty function mechanism is introduced to effectively reduce the probability of the mobile robot falling into the local optimal.The improved variable-step ant colony algorithm greatly improves the path search capability,which is suitable for path planning of mobile robots in different complex scenarios.Finally,a mobile robot experimental platform based on ROS was built,and the hardware structure and software structure of the mobile robot were designed for path planning,which further verified the effectiveness of the improved variable-step ant colony algorithm in path planning.