Indoor Intelligent Vehicles' Path Planning Based On Multi-objective And Dynamic Environment

With the development of robotics,mobile robots are more and more widely used in industry and daily life.The robots face more and more complicated environments and need more and more interactions.The path planning of mobile robots is the main content of the research,and it is of great significance.In this paper,the research of indoor intelligent vehicle path planning in multi-objective and dynamic environment is carried out.The goal is to propose an improved algorithm for path planning of multiple continuous target points in dynamic environment.This paper first introduces the development of mobile robot,the research status of the path planning,the main algorithms of the global path planning and local path planning and briefly introduces their advantages and disadvantages.The basic concepts and characteristics of the ROS system are briefly introduced.At the same time,for the realization of SLAM map construction and localization in ROS,the use of indoor 2D radar sensors and the working status of "hector_mapping" package are introduced.For the purpose of path planning and navigation ROS,introduces the overall framework of "move_base" package and the function of each function module in the package.On the basis of this,the experimental research scheme based on ROS system is givenThen,the path planning algorithm is improved.Based on the traditional A*algorithm,the global path planning algorithm is proposed to obtain the optimal path using the improvement of the extension point rule and the backtracking path.The dynamic weight heuristic function based on the potential field method is improved to improve the performance of the algorithm.MATLAB simulation experiments are carried out in the improved process and the improved algorithm.The expansion of the simulation results,the number of access nodes,the path length and the average time-consuming are compared and analyzed,which proves that the improved algorithm is in line with expectations aims.The improved algorithm is designed to realize the path planning of multiple consecutive target points.The local path planning algorithm analyzes the kinematics model,speed sampling constraints and evaluation function of the indoor smart car in the basis of the DWA(Dynamic Window Approach)algorithm.The improvement of the obstacle expansion zone processing and abnormal status processing is proposed.It realizes the path planning based on the improved DWA algorithm in dynamic environment.Finally,the global path planning algorithm and the local path planning algorithm are combined to propose an improved path planning algorithm based on dynamic environment and multi-objective.Select the appropriate experimental equipment and set up the experimental site,using the indoor three-wheeled omnidirectional ROS smart car to verify the correctness of the improved algorithm.The experiment results show that the improved path planning algorithm can make the optimal path planning for multiple target points.In addition,the algorithm can deal with the dynamic obstacles in the path planning process,and re-planning the path,then reach the remaining targets.