| In recent years,the application of robotics in industrial production,intelligent manufacturing,military and other fields has become more and more extensive and deeper.The ground-based mobile robot,as the most common form among all kinds of robots,its autonomous navigation ability has become an important technical component.This paper focuses on autonomous navigation robots,and researches on simultaneously localization and map construction technology and robot localization and path planning navigation technology.Using a depth camera instead of a single-line lidar as the main sensor,then designs an autonomous navigation method in indoor environment of mobile robot,then uses Turtlebot2 mobile platform to carry out the relevant experiments.First of all,the software and hardware experimental platform of the robot platform used in this subject is introduced,then establishes the system model of the selected robot platform.In the plane environment,the motion model and sensor observation model are established according to the kinematics of the motion robot.Secondly,the SLAM technology of mobile robots is studied.In this paper,the occupancy grid map is used to represent the map.The traditional RBPF-SLAM algorithm is studied and analyzed.In order to solve the problem of excessive calculation caused by frequent resampling of particles and the decrease of particle diversity caused by resampling process in the traditional algorithm,this paper uses an improved algorithm which combines the latest observation information of the sensor with the robot motion model as a proposal distribution and uses an adaptive resampling method at the same time to construct the environmental map.Finally and finally verifies the practicability of the algorithm by simulation experiments.Thirdly,the technology of robot localization and path planning is studied.According to the indoor environment occupancy grid map which has been constructed,an Adaptive Monte Carlo algorithm based on particle filter is selected to locate and estimate the position of robot.Path planning mainly consists of global path planning and local path planning.The Dijkstra algorithm,A* algorithm,and DWA algorithm principles are introduced in detail;the deficiencies of the DWA dynamic window method are improved.Then,by establishing simulation experiments,the feasibility of the improved algorithm is verified.Finally,build an experimental platform for autonomous navigation robot.The SLAM technology,localization technology and path planning technology of robot during navigation process are analyzed experimentally,the effectiveness and robustness of the system are verified.The experiment proves that the system can successfully complete the autonomous navigation task of the mobile robot in the indoor environment. |
