The Simulation And Realization Of Mobile Robot Path Planning

Mobile robot has a wide application prospect in space exploration,ocean development,factory automation,insurance,military,service,etc.Among them,path planning technology is one of the core contents of mobile robot research,so the study of path planning has important application value,but there are many practical problems to be solved:firstly,mobile robots are widely used in a variety of different scenarios,so that the study of path planning must also extend from a known static environment to a more complex environment,analysis of a safe and effective path in complex environments is a hot issue in current path planning;secondly,the existing algorithm is not suitable for path planning in complex environment.So in this process of learning and improvement of these algorithms,completed the complex environment of the mobile robot path planning experiments,the results are as follows:1.A hybrid algorithm based on firefly and genetic algorithm is proposed for TSP.The firefly algorithm is improved by introducing the genetic algorithm in the cross,mutation,reverse operation.The simulation experiment is carried out in MATLAB,the results show that this hybrid algorithm can make up the randomness of the genetic algorithm and overcome the precocious phenomenon that the firefly algorithm may appear in the convergence process.At the same time,the convergence rate of the firefly algorithm is increased.2.Aiming at the problem of path planning in static environment,an improved niche firefly algorithm is proposed.Firstly,the mathematical model of the firefly algorithm is redefined according to the characteristics of the grid map.Secondly,the introduction of niche technology,through the niche technology sharing mechanism,to speed up the convergence rate of the algorithm.Then,considering the size of the actual robot,we propose an improved niche firefly algorithm to obtain the globally unique optimal path by increasing the constraint condition of the optimal solution and setting the safe distance constraint.Finally,the simulation experiment is carried out in MATLAB.The results show that the improved niche firefly algorithm has excellent convergence and feasibility.3.Aiming at the problem of path planning in complex environment,this paper proposes a hybrid algorithm based on improved firefly algorithm and improved artificial potential field method.First of all,in order to make the artificial field method more adapt to the environment of dynamic obstacle,on the basis of the traditional repulsive field function,a new repulsive field is established for the dynamic obstacle,so that the robot can effectively avoid the dynamic obstacles.Secondly,the hybrid algorithm combines the improved firefly algorithm for global path planning and the improved artificial potential field method for local path planning,which not only solves the problem of lack of real-time in global path planning,at the same time,because of a global reference path,the computational complexity is reduced in local path planning.Finally,the feasibility of the hybrid algorithm is verified by simulation experiments.4.The realization of mobile robot path planning is studied.First,the mobile robot hardware platform was design.Secondly,according to the kinematics model of the robot,the non-linear model predictive control algorithm is used to track the path,simulation results show that the nonlinear model predictive control has good tracking effect.Finally,the path planning and tracking process is completed on the wheeled robot.The experimental results show that the proposed mobile robot path planning scheme is effective and feasible.