Robot Path Planning Based On Improved Ant Colony Algorithm With Potential Field Heuristic

In recent years,with the rapid development of robot technology,the field of mobile robot appeared widely in daily life,people demand for mobile robot safety and efficiency are increasingly high,which makes the relevant technical issues of mobile robot research is more prominent.Robot path planning is one of the most important technologies in the field of mobile robot research.This paper mainly discusses the problem of path planning of mobile robot,and also relates to the environment modeling and mobile robot localization problem,and set up a simple experimental platform of mobile robot with a four wheel,on the basis of the path planning of mobile robot global environment known experiment.The main contents include the following several points:(1)In view of the problem of grid method in the environment modeling,the edge optimization is adopted and the adjacency matrix is designed.The mobile robot can find the way in the grid graph with octree mode,which improves the security and reliability of the mobile robot with the grid method modeling.(2)Combine the positioning requirements of the indoor mobile robot in this article.The positioning method based on dead reckoning was analyzed.According to the positioning error caused by its long-time positioning,an ultrasonic distance-finding assisted dead reckoning scheme was designed.The positioning scheme is simple and easy,and overcomes the cumulative error problem of dead reckoning.(3)Aiming at the limitations of ant colony algorithm in path planning.An improved ant colony algorithm with potential field heuristic is proposed.The algorithm mainly improves the following three aspects: First,The algorithm constructs the comprehensive heuristic information based on the initial path obatined by artificial potential field and the distance between the robot and the next node.Moreover,the heuristic information decline coefficient is introduced to avoid the local optimization problem caused by misleading information of the traditional ant colony algorithm.Second,Based on the zero point theorem,the principle of unequal distribution of initial pheromone is proposed.Various grid positions are endowed with different initial pheromones,which decreases the blindness of ant colony search and improves the searching efficiency of the algorithm.Third,an iterative threshold is set to adaptively adjust pheromone volatilization coefficients.In this way,the excellent global searching ability is achieved,and the stagnation phenomenon can be avoided.The simulation results show the effectiveness of the method proposed in this paper.(4)The experiment platform of mobile robot is designed.Using the hardware resources such as Raspberry Pi processor module,L298 N motor drive module and HC-SR04 ultrasonic distance measuring module,the mobile robot experimental platform is built.At the same time,the software control of each module is designed.The indoor path planning is carried out with the improved ant colony algorithm proposed by this paper.Experiment results show that the algorithm is feasible and effective.