Research On Path Planning Of Mobile Robot Based On Improved RRT Algorithm

In recent years,with the rapid development of mobile robots in various industries such as service,military,and entertainment,researching on mobile robots has gained more attention from social enterprises and research institutes.As a key technology in the field of mobile robot research,the quality of the algorithm of the path planning technology has a direct impact on the degree of intelligence and autonomy of mobile robot.Therefore,the research about path planning algorithm has very important practical significance.Mobile robot path planning mainly considers the problem of accuracy and real-time,but lots of traditional path planning algorithms can only satisfy one of them.Therefore,this paper will improve the planning efficiency and path quality respectively based on the Rapidly-exploring Random Tree(RRT)algorithm,which can meet the requirements of mobile robots to complete path planning tasks in high efficiency and high quality under different environments.Firstly,this paper analyzes the kinematics model of wheeled mobile robots.On this basis,demonstrating the non-integrity,controllability and local stability of mobile robots to provide a reliable theoretical support for the improvement of algorithm.Secondly,in view of low efficiency of RRT algorithm planning,the introduction of Goal Biasing RRT(GBRRT)algorithm makes the search has some enlightenment.When facing complex environment,three optimization methods are adopted based on the GB-RRT algorithm.The first method adopts the Repeat-out Detection mechanism,which can solve the problem that the original algorithm is easy to fall into the local minimum value.The second is to use the Manhattan distance measurement method,which can reduce the complexity of the algotithm.The third adds the Adjacent Random Point function,which can reduce the amount of calculation.Finally,using an improved RRT algorithm based on A~* guiding field.Basedon the optimality and completeness of A~* algorithm,this method plans a low-resolutiongrid path by using A~* algorithm,then generate a set-width guiding field around the path.The expansion of Improved Goal Biasing RRT(IGB-RRT)is limited in this guiding field,so that the planned path approximates the optimal solution.In this paper,the simulation experiments in different environments prove that the IGBRRT algorithm in the more complex environment,the shorter the relative planning time,the higher the efficiency,it is verified that the path quality about IGB-RRT based on A~*guiding field is approximated to the optimal solution.The research in this paper has different degrees of optimization from both planning efficiency and path quality,and has certain reference value for mobile robot path planning research.This paper contains 26 maps,12 tables,and 57 references.