Research On Key Technologies Of Autonomous Navigation For Mobile Robots

With the intelligent upgrading of traditional industries,there is an urgent need for intelligent mobile robots in traditional fields such as warehousing,service,and healthcare.Among them,autonomous navigation is one of the core issues that limits the widespread application of intelligent mobile robots.Based on the SLAM navigation scheme,this study focuses on the two core issues of environmental perception and path planning during navigation.The research takes a mobile robot with an Ackermann chassis structure as the object of study,and with the help of the ROS,carries out research on Cartographer map construction based on laser radar,the AMCL algorithm positioning,improved global path planning using the A* algorithm,and improved local path planning using the DWA.The performance of the autonomous navigation system was tested in real indoor environments.The research work of this paper is as follows:(1)Theoretical modeling of an autonomous navigation system for a mobile robot based on the Ackermann chassis.Firstly,a kinematic model of the mobile robot was established,including the Ackermann kinematic model and the odometry model,to control the motion of the mobile robot and calculate its pose.Secondly,a mathematical model of the laser radar was established,including range model and observation model,to collect obstacle information in the environment.Finally,the construction method of occupied grid map was analyzed in detail,which provided a theoretical basis for building a 2D grid map afterwards.(2)Research on the environment perception module of mobile robot autonomous navigation system.Firstly,in order to solve the problem of map construction in an unknown environment,the Cartographer algorithm was used for simulation experiments and compared with two other popular SLAM algorithms.Secondly,f for the relocalization problem in a known environment,the AMCL algorithm was used for localization,and simulation experiments were conducted on the environment map established by the Cartographer algorithm.Finally,based on the Cartographer and AMCL algorithms,a complete environment perception module was designed.(3)Research on path planning module of autonomous navigation system for mobile robots.Firstly,to address the issues of non-smooth and multi-turn paths in global path planning algorithms,an improved A* algorithm was proposed.This algorithm enhances the smoothness of the path by expanding the search method of the neighborhood,and introduces a path turning factor to solve the problem of multiple turns.Secondly,in order to the problem that global path planning algorithms cannot adapt to dynamic environments,the DWA algorithm was introduced for local path planning.However,as the DWA algorithm suffers from the issue of local optimality,a global path evaluation function was added to improve the DWA algorithm,and the improved A* algorithm and improved DWA algorithm were integrated to address the problem of local optimality.Finally,a complete path planning module was designed based on the global path planning algorithm and local path planning algorithm.(4)Experimental research on the autonomous navigation system of a mobile robot in indoor environments.On the one hand,a mobile robot test platform with Ackermann chassis was designed,including hardware construction and software development,and an autonomous navigation system was integrated on the Ackermann mobile robot platform.On the other hand,autonomous navigation functional tests were conducted in a home indoor environment.The experimental results verified the reliability and practicality of the autonomous navigation system designed in this paper in practical applications.