Path Planning Of Mobile Robot Based On D~* Algorithms

With the development of science and technology,various types of mobile robots play an important role in the field of human beings.The quality of autonomous navigation is the core index of mobile robots,and path planning as one of the key technologies of autonomous navigation has been widely studied.This thesis studies the path planning problem of indoor mobile robots.Aiming at some shortcomings of the traditional heuristic algorithm D*algorithm,the thesis improves the overall quality of the path under the similar planning effect.Using the simulation environment of MATLAB,the path planning technology based on D*algorithm is studied.The main contents of this thesis are as follows:Firstly,various path planning algorithms for mobile robots are introduced.The advantages and disadvantages of these algorithms are analyzed in detail.At the same time,the achievements of various scholars in recent years are summarized.Based on the research and analysis of various path planning algorithms,D*algorithm is chosen as the main content of this thesis.D*algorithm has some advantages that other heuristic algorithms do not have,but also some shortcomings.This thesis proposes to improve the heuristic function of traditional D*algorithm and the extension mechanism of sub-nodes.D*algorithm is a length-first algorithm,which improves on maintaining the good path length of the original algorithm.The planning speed,turning times and degrees are improved and optimized,and the path security is greatly improved,so that the practicability of the algorithm is enhanced.When there are more than one path objective,it involves a shortest traversal problem,namely TSP problem.However,the improved D*algorithm in the previous thesis does not have the ability to deal with TSP problem.Therefore,the ant colony optimization algorithm(ACO)is introduced to deal with TSP problem,which has strong robustness and good convergence speed.However,in path planning,the planning speed is much slower than other heuristic algorithms and can not reach it.Therefore,this thesis proposes an improved D*algorithm based on ACO fusion.The two algorithms complement each other.On this basis,the problem of multi-objective search is solved.It has a certain reference significance for small-scale post-disaster rescue,mine clearance and agricultural planting mobile robots.Finally,the dynamic obstacles in map environment are studied.Based on the principle of rolling window,the improved D*algorithm is used to plan the global path.Then,in the mobile robot,the types of obstacles that may come are predicted in every cycle of rolling window,and the avoidance schemes are selected.At the same time,the improved D*algorithm is used to plan the local path to achieve the mobile.Perfect handling of dynamic obstacles in robot traveling.