论文标题
视觉语义大满贯，带有地标的大规模室外环境
Visual Semantic SLAM with Landmarks for Large-Scale Outdoor Environment
论文作者
论文摘要
语义大满贯是自主驾驶和智能代理的重要领域，它可以使机器人能够完成高级导航任务，获得简单的认知或推理能力并实现基于语言的人类机器人交流。在本文中，我们构建了一个系统来创建语义3D地图，通过将ORB SLAM的3D点云与大规模环境中的卷积神经网络模型PSPNET-101相结合的3D点云与语义分割信息。此外，已经构建了一个针对Kitti序列的新数据集，其中包含来自序列相关街道的Google Map中的GPS信息和标签。此外，我们找到了一种将现实世界地标与点云图相关联的方法，并基于语义图构建了拓扑图。
Semantic SLAM is an important field in autonomous driving and intelligent agents, which can enable robots to achieve high-level navigation tasks, obtain simple cognition or reasoning ability and achieve language-based human-robot-interaction. In this paper, we built a system to creat a semantic 3D map by combining 3D point cloud from ORB SLAM with semantic segmentation information from Convolutional Neural Network model PSPNet-101 for large-scale environments. Besides, a new dataset for KITTI sequences has been built, which contains the GPS information and labels of landmarks from Google Map in related streets of the sequences. Moreover, we find a way to associate the real-world landmark with point cloud map and built a topological map based on semantic map.
