Particle Filter-based Localization of a Mobile Robot by Using a Single Lidar Sensor under SLAM in ROS Environment
Particle Filter-based Localization of a Mobile Robot by Using a Single Lidar Sensor under SLAM in ROS Environment
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ROS 环境下基于 SLAM 的单个激光雷达传感器的移动机器人基于粒子滤波器的定位
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Seul Jung
中科院分区：
文献类型：
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作者：
D. Talwar;Seul Jung
自主移动机器人中最受欢迎的问题之一是映射、定位和自主导航。本文将自适应蒙特卡罗定位（AMCL）作为粒子滤波方法，展示了它在室内环境中对移动机器人的有效定位。仿真过程中，机器人在Gazebo和Rviz环境中实现了定位和自主导航。仿真结果表明，滤波器中的粒子快速收敛于姿态，机器人能够成功地沿着路径到达目标位置。对移动机器人在静态和动态两种不同环境下的定位进行了仿真。机器人每次都能成功地到达目标。仿真结果表明，AMCL在这些环境下具有良好的性能。
One of the most popular issues in autonomous mobile robots is mapping, localizing and autonomous navigation. In this paper, Adaptive Monte Carlo Localization (AMCL) as particle filters method is presented to show how effectively it localizes the mobile robot in an indoor environment. During the simulations, the robot is localized and autonomously navigates in Gazebo and Rviz environment. The simulation results demonstrated that the particles in the filter quickly converge on the pose and the robot was successfully able to follow the path to reach its goal position. Simulations for a mobile robot to be localized in two different environments, static and dynamic, were carried out. The robot was successful in reaching its goal every time. Simulation results thus point out that AMCL performed effectively in these environments.