The Research On Robot Path Planning Method

The rapid development of the microelectronics industry has made robots gradually enter the daily life of human beings.In the research of many fields of mobile robots,the research of path planning is also very necessary.The problem of path planning involves computer visual perception,data processing,Interdisciplinary knowledge such as motor control and computer control.Although many scholars have proposed various algorithms to solve this problem,for example,a combination of various intelligent algorithms has been studied more and more.The combined algorithm has many advantages,and it complements each other to make the algorithm more intelligent and more adaptable to unfamiliar environments.However,there are not many effective methods.This is the necessity of continuing to study the path planning problem.On the basis of all kinds of path planning algorithms put forward by predecessors,the advantages and disadvantages of various algorithms are summarized in order to achieve complementary advantages between the algorithms.After describing the advantages and disadvantages of the artificial potential field method and ant colony algorithm,this paper improves the two algorithms,and then combines them to get the potential ant colony algorithm.Firstly,the advantage and disadvantage of the traditional artificial potential field method and its mathematical model are expounded,and an improved scheme is proposed to solve the problems of local minima in the process of robot moving,which is verified in detail.Secondly,aiming at the initial ant colony algorithm,this paper improves the initial pheromone distribution and security information of the algorithm,improves the efficiency of the ant colony algorithm and reduces the probability of ant deadlock.Furthermore,the potential field method and ant colony algorithm are combined to enhance the effect of potential field force at the initial stage and reduce the influence of weak field force at the later stage,so as to increase the searching ability of ant colony algorithm at the initial stage,thereby shortening the time consumed by the whole algorithm of path searching,and avoiding the premature convergence of path length,and finding the optimal path at the most.Finally,the algorithm is verified by MATLAB,and the path and calculation time are obtained to verify the rationality and correctness of the algorithm.