Visual-Based Semantic SLAM with Landmarks for Large-Scale Outdoor Environment
2019 2nd China Symposium on Cognitive Computing and Hybrid Intelligence (CCHI)(2019)
摘要
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 [1], [2] with semantic segmentation information from Convolutional Neural Network model PSPNet-101 [3] for large-scale environments. Besides, a new dataset for KITTI [4] 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.
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关键词
Semantic SLAM,Visual SLAM,Large-Scale SLAM,Semantic Segmentation,Landmark-level Semantic Mapping
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