| With the rapid development of science and technology,in order to meet the growing demand for automation and artificial intelligence in military,industrial,and civil use,robots continue to enter more fields.As a branch with broad application prospects,mobile robots have attracted the attention of various research institutions.Among them,one of the most concerned research hotspots and difficulties is the Simultaneous Localization And Mapping(SLAM)problem of mobile robots.It is the key issue to solve the autonomous navigation of mobile robots.It solves the problem of SLAM.The mobile machine can perform autonomous navigation and movement to perform more complex tasks,such as field search and rescue,indoor transport,multirobot cooperative movement,etc.,due to its strong application value.It has been widely studied by scholars at home and abroad.In this paper,an autonomous mobile mobile robot platform is combined to solve the grid map creation and navigation problems in the SLAM problem by using particle filter algorithms.This article focuses on the following aspects:First,the research background and domestic and foreign research status of mobile robots and SLAM related technologies are briefly introduced,and various probabilistic models of mobile robot control systems are introduced.The overall construction of the mobile robot system is described in general.The hardware platform construction and the overall software design framework are described in detail.Secondly,the research on SLAM technology using Lidar is described in detail.The particle filter algorithm and the application of Rao-Blackwell particle filter algorithm in SLAM are introduced in detail.Through the theoretical analysis and the simulation of the algorithm in the Matlab simulation environment,the effectiveness of the algorithm in solving the SLAM problem is verified,and the theoretical support for the algorithm of the navigation and mapping software is provided.Then,corresponding control software is designed for the mobile robot system to be built,which is mainly divided into lower-level motion control software,laser radar data acquisition software,video stream acquisition software,upper computer map creation and navigation software,and mobile end monitoring software.section.The overall control of the mobile robot system is experimented by the prepared control software.Finally,the RBPF-SLAM algorithm is validated with the self-constructed mobile robot and system control software.At the same time,a comprehensive experiment is also performed on the use of the self-written control software modules.Through the analysis of the experimental results,the validity of the algorithm and the ease of use and practicality of the mobile robot construction and navigation software of the host computer are verified. |
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