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This repo contains the code for our RSS2020 paper: OverlapNet - Loop Closing for 3D LiDAR-based SLAM. More Related Work OverlapNet - Loop Closing for 3D LiDAR-based SLAM start the processing of the scans via the "play button" in the GUI.open a Velodyne directory from the KITTI Visual Odometry Benchmark and select a ".bin" file,.run visualizer in the bin directory by.To use SuMa++ with your own dataset, you may finetune or retrain the semantic segmentation network.Īll binaries are copied to the bin directory of the source folder of the project.SuMa++ now can only work with KITTI dataset, since the semantic segmentation may not generalize well in other environments.
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For the first time using, rangenet_lib will take several minutes to build a.You need to specify the model path in the configuration file in the config/ folder.Before running SuMa++, you need to first build the rangenet_lib and download the pretrained model.~/catkin_ws/src/semantic_suma) should contain a bin directory containing the visualizer. If you have a NVIDIA device, like a Geforce or Quadro graphics card, you should also activate the NVIDIA extensions using -DENABLE_NVIDIA_EXT=YES for info about the current GPU memory usage of the program.Īfter this setup steps, you can build with catkin build, since the configuration has been saved to your current Catkin profile (therefore, -save-config was needed). If you are unsure you can also leave it on the default version 330, which should be supported by all OpenGL-capable devices. Here the line OpenGL core profile version string: 4.3.0 NVIDIA 367.44 is important and therefore you should use -DOPENGL_VERSION = 430. OpenGL shading language version string: 4.50 NVIDIA OpenGL version string: 4.5.0 NVIDIA 367.44 OpenGL core profile shading language version string: 4.30 NVIDIA OpenGL core profile version string: 4.3.0 NVIDIA 367.44