Research on the Methodology of Autonomous Mobile Robot Localization and Navigation in Unknown Enviroments
|School||Southwest Jiaotong University|
|Course||Mechanical and Electronic Engineering|
|Keywords||Autonomous Mobile Robot Localization and Navigation Behavior ParticleFilter Simultaneous Localization and Mapping (SLAM)|
Research on localization and navigation of autonomous mobile robot is an important problem in the robot research field. For mobile robot, how to build hardware carrier, how to implement accurate control, and how to characterize localization and navigation are focal and difficult points in the mobile robot research.Firstly, the background and significance of mobile robot are introduced in this paper, and the localization and navigation of mobile robot have been discussed in depth. Afterwards, starting with the establishment of system models, the ontology model, sensor model and environment model of mobile robot are deeply researched and discussed. And then the hardware structure and basic software driver are designed and produced for mobile robot, which provides a reliable development platform for the implement of high-level behaviors and intelligent control in mobile robot system.Secondly, the production mechanism of mobile robot behaviors and navigation strategy based on behaviors are analysed and researched in this paper. Four typical behaviors of mobile robot are summarized. Behaviors, such as obstacle avoidance, wall-following, tracking and following, are implemented and simulated in the hardware platform of mobile mechanical mouse and homemade mobile car.In view of the trend and hot of mobile robot localization and navigation, autonomous mobile robot SLAM in indoor unknown environments is deeply researched in this paper. Federated SLAM algorithm based on target extraction-data association-particle filter is put forward. SLAM experiments in the Matlab simulation environment show the effectiveness of the proposed method.At last, the whole research commitment is summarized. And the research foreground of localization and navigation in unknown environments and SLAM is also given.