In this work, we present a comparative analysis of the trajectories estimated from various Simultaneous Localization and Mapping (SLAM) systems in a simulation environment for vineyards. Vineyard environment is challenging for SLAM methods, due to visual appearance changes over time, uneven terrain, and repeated visual patterns. For this reason, we created a simulation environment specifically for vineyards to help studying SLAM systems in such a challenging environment. We evaluated the following SLAM systems: LIO-SAM, StaticMapping, ORB-SLAM2, and RTAB-MAP in four different scenarios. The mobile robot used in this study equipped with 2D and 3D lidars, IMU, and RGB-D camera (Kinect v2). The results show good and encouraging performance of RTAB-MAP in such an environment.
翻译:在这项工作中,我们对葡萄园模拟环境中各种同声定位和绘图(SLAM)系统估计的轨迹进行了比较分析,由于随着时间的推移目视变化、地形不均和反复的视觉模式,植物园环境对SLM方法具有挑战性,因此,我们专门为葡萄园创造了模拟环境,以帮助在这种具有挑战性的环境中研究SLAM系统。我们评估了以下SLM系统:LIO-SAM、StaticMapping、ORB-SLAM2和RTAB-MAP, 四种不同的情况:这项研究中使用的移动机器人,配有2D和3D Lidars、IMU和RGB-D摄像机(Kinect v.2),结果显示RTAB-MAP在这种环境中的良好和令人鼓舞的表现。