# Online_Semantic_SLAM **Repository Path**: sdkmsdn_admin/Online_Semantic_SLAM ## Basic Information - **Project Name**: Online_Semantic_SLAM - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2020-03-29 - **Last Updated**: 2023-04-02 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # OS-SLAM **Authors:** Li Wenqiang **Date:** **19 March 2019** OS-SLAM is Online Semantic SLAM mostly based on great ORB-SLAM2,aimed to using semantic information improve performance ; Now we've finished semi-dense point cloud creation based on window optimize . Still working on use semantic information to pick out dynamic points; In future ,we will use the SLAM output refining the segment and backpropagate to DL model online; # Prerequisites We have tested the library in **Ubuntu 12.04**, **14.04** and **16.04**, but it should be easy to compile in other platforms. A powerful computer (e.g. i7) will ensure real-time performance and provide more stable and accurate results. ## C++11 or C++0x Compiler We use the new thread and chrono functionalities of C++11. ## Pangolin We use [Pangolin](https://github.com/stevenlovegrove/Pangolin) for visualization and user interface. Dowload and install instructions can be found at: https://github.com/stevenlovegrove/Pangolin. ## OpenCV We use [OpenCV](http://opencv.org) to manipulate images and features. Dowload and install instructions can be found at: http://opencv.org. **Required at leat 2.4.3. Tested with OpenCV 2.4.11 and OpenCV 3.2**. ## Eigen3 Required by g2o (see below). Download and install instructions can be found at: http://eigen.tuxfamily.org. **Required at least 3.1.0**. ## DBoW2 and g2o (Included in Thirdparty folder) We use modified versions of the [DBoW2](https://github.com/dorian3d/DBoW2) library to perform place recognition and [g2o](https://github.com/RainerKuemmerle/g2o) library to perform non-linear optimizations. Both modified libraries (which are BSD) are included in the *Thirdparty* folder. ## ROS (optional) We provide some examples to process the live input of a monocular, stereo or RGB-D camera using [ROS](ros.org). Building these examples is optional. In case you want to use ROS, a version Hydro or newer is needed.