Research On Mobile Service Robot Positioning And Mapping Simultaneously

With the development of science and technology,the hardware market and software development of mobile robots have gradually matured,making it possible for mobile robots to be applied on a large scale.Especially with the popularity of robots in various industries,the working environment of mobile robots is becoming more and more complex,which puts forward higher requirements on the ability of mobile robots to complete various tasks.Therefore,improving map construction and it`s own positioning the accuracy has become a research hotspot to mobile robots.Most research on robot mapping and positioning are still independent of each other,this kind of research makes the mobile robot's software and hardware change,the mobile robot's positioning and mapping system faces secondary development.In order to improve the reuse rate of robot's R&D code,ROS(Robot Operating System)is used as the software platform in this paper to study the most critical Simultaneous Localization And Mapping(SLAM)for mobile Robot navigation in static unknown environment.Firstly,the extended kalman filter(EKF)and unscented kalman filter(UKF)are studied,and the particle filter(PF)is improved through unscented transformation,so that the particle filter has better performance in non-gaussian nonlinear estimation.The UKF and improved PF were introduced into the fastSLAM,and the algorithm flow of the improved fastSLAM was given.The accuracy of the improved fastSLAM for positioning and the estimation of road sign was compared through simulation.Secondly,the mobile service robot is built with self-selected hardware.The robot various hardware functions and software development and control are introduced.The parameters of the lidar and the lidar coordinate system are studied.The speed and Angle control of wheel and the mathematical model of mobile robot are given.Finally,the simulation of fastSLAM algorithm and the improvement of fastSLAM algorithm are carried out in Stage,and the building robot is used to verify the construction and positioning accuracy in real environment,and the two algorithms data are compared.To verify the improved fastSLAM algorithm`s feasibility and accuracy.