Simultaneous Localization and Mapping of Mobile Robot using GMapping Algorithm

被引：2
作者：
Revanth, Marshal C. [1 ]
Saravanakumar, D. [2 ]
Sakthivel, G. [2 ]
Jegadeeshwaran, R. [1 ]
机构：
[1] Vellore Inst Technol, Sch Mech Enginnering, Chennai Campus, Chennai, Tamil Nadu, India
[2] Vellore Inst Technol, Ctr Automat, Chennai Campus, Chennai, Tamil Nadu, India
来源：
2020 6TH IEEE INTERNATIONAL SYMPOSIUM ON SMART ELECTRONIC SYSTEMS (ISES 2020) (FORMERLY INIS) | 2020年
关键词：
SLAM; GMapping; RBPF; Robot Operating System; LIDAR;
D O I：
10.1109/iSES50453.2020.00024
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
The main aspect of the mobile robot system is the ability to localize itself accurately and simultaneously, create an map of the unknown environment. Simultaneous localization and mapping (SLAM) is required for autonomous navigation. The framework of SLAM is based on Rao-Blackwellized Particle Filter (RBPF) that is applied through GMapping algorithm. The 2D LIDAR seamier and odometer is used as main sensor in the simulated robot model. The RBPF algorithm and the data of the LIDAR and odometer are fused to create the 2D map of the simulated environment as well as localization and navigation of the robot in unknown environment. Experiment Implementation is carried in Robotic Operating system (ROS) and gazebo simulator.
引用
收藏
页码：56 / 60
页数：5
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