ROS based service robot platform

Ruchik Mishra, A. Javed
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引用次数: 43

Abstract

The substitution of a human factor by an affordable low-cost robotic system has been increasing recently. The reason being, the robot is expected to do less errors than a human does and does not have a will of its own. This paper proposes a service robot platform that is capable of mapping, localizing itself and navigating in an indoor environment and is best suited for structured environment with static obstacles. The approach used for mapping is a ROS package which is a ROS wrapper of Real Time Appearance Based Mapping with the help of a low cost RGB-D camera, the Microsoft Kinect XBOX 360 with a turtlebot robot model for visualization. RTAB-Map takes into account loop closure in real time constraints with a memory management technique which makes the mapping process independent of time and size. Once the mapping is done and the 2D projection of the map is obtained of our real indoor environment of the lab, the simulation of the autonomous navigation of the robot model to the desired location is done on Gazebo. For the navigation to happen successfully, Adaptive Monte Carlo Localization is used for localizing the turtlebot model in the map. The simulation results were visualized using rviz and were found to be satisfactory.
基于ROS的服务机器人平台
最近,廉价的机器人系统取代人为因素的趋势越来越明显。原因是,人们期望机器人比人类犯更少的错误,而且机器人没有自己的意志。本文提出了一种能够在室内环境中进行测绘、定位和导航的服务机器人平台,该平台最适合于具有静态障碍物的结构化环境。用于绘图的方法是一个ROS包,这是一个实时外观基于映射的ROS包装器,借助低成本的RGB-D相机,微软Kinect XBOX 360和一个可视化的乌龟机器人模型。RTAB-Map使用内存管理技术考虑了实时约束中的循环闭包,这使得映射过程与时间和大小无关。一旦绘制完成,并获得我们实验室真实室内环境的二维地图投影,就可以在Gazebo上进行机器人模型自主导航到期望位置的仿真。为了使导航成功进行,使用自适应蒙特卡罗定位(Adaptive Monte Carlo Localization)来定位地图中的乌龟模型。利用rviz对仿真结果进行了可视化处理,结果令人满意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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