The Implementation of the SLAM Method in ROS System and Underwater Robot

Fei Suo, Jiaqi Lv, Zhan Wang
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Abstract

Autonomous localization and map construction of underwater robots in unknown environments is a very important research area. Visual SLAM technology is based on visual processing algorithms and can accomplish this task at a low cost. This paper focuses on a set of underwater robot visual SLAM experimental process. Based on ROS system, Mono visual SLAM experiments are performed on UWSim simulation environment and real robot respectively by using mature ORB-SLAM2 algorithm. The experimental results show that this method can accurately build the sparse point cloud map of the environment under the condition of sufficient environmental feature points.
SLAM方法在ROS系统和水下机器人中的实现
水下机器人在未知环境下的自主定位与地图构建是一个非常重要的研究领域。视觉SLAM技术基于视觉处理算法,可以以较低的成本完成这一任务。本文主要研究了一套水下机器人视觉SLAM的实验过程。基于ROS系统,采用成熟的ORB-SLAM2算法,分别在UWSim仿真环境和真实机器人上进行了单视觉SLAM实验。实验结果表明,该方法可以在环境特征点充足的情况下,准确地构建环境的稀疏点云图。
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