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LIO_SAM for 6-axis IMU and GNSS.
| Date | Stars |
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| 2026-07-24 | 853 |
| 2026-07-25 | 853 |
| 2026-07-28 | 853 |
| 2026-07-30 | 853 |
| 2026-08-06 | 853 |
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 # LIO_SAM_6AXIS LIO_SAM_6AXIS is an open-source SLAM project based on the project [LIO_SAM](https://github.com/TixiaoShan/LIO-SAM) that has been modified to support a wider range of sensors. It includes support for a 6-axis IMU and low-cost GNSS, making it easier to adapt for your own sensor setup. <img src="README/image-20220609035032131.png" alt="image-20220609035032131" style="zoom: 67%;" /> ## Features LIO_SAM_6AXIS includes the following features: - Support for a 6-axis IMU: This allows you to use orientation information in state estimation, improving the accuracy of your results. - Support for low-cost GNSS: By eliminating the need to adapt for the robot_localization node, this feature makes it easier to integrate GNSS into your SLAM system. - GPS constraint visualization: This feature helps with debugging by allowing you to visualize the GPS constraints that are being used in the optimization. ## Latest News(2025-05-23) - Currently, it is challenging to make significant improvements and enhancements based on this framework. We strongly recommend using [MS-Mapping](https://github.com/JokerJohn/MS-Mapping) for mapping with **better accuracy and robustness**; you only need to set `useMultiMode = false`. Additionally, multi-session mapping is supported, and a Docker environment is available for configuration. .png) ## Getting Started To get started with LIO_SAM_6AXIS, follow these steps: 1. Clone the repository: ```bash git clone https://github.com/JokerJohn/LIO_SAM_6AXIS.git ``` 2. Install the dependencies: ```bash cd LIO_SAM_6AXIS catkin build ``` 3. Launch the roslaunch file for your sensor setup: ```bash # set your bag_path here roslaunch lio_sam_6axis test_vlp16.launch ``` For more information on how to use LIO_SAM_6AXIS, see the video tutorial and documentation. 4. finally, save your point cloud map. ```bash # map is in the LIO-SAM-6AXIS/data rosservice call /lio_sam_6axis/save_map ``` <img src="README/image-20220609044824460.png" alt="image-20220609044824460" style="zoom: 80%;" /> 5. for docker support. `Dockerfile` is for people who don't want to break their own environment. ```bash # please cd the folder which have Dockerfile first, approximately 10mins based on your internet and CPU docker build -t zhangkin/lio_sam_6axis . docker run -it --net=host --gpus all --name lio_sam_6axis zhangkin/lio_sam_6axis /bin/zsh # OR -v to link the folder from your computer into container (your_computer_loc:container_loc) docker run -it --net=host --gpus all --name lio_sam_6axis -v /home/kin/bag_data:/home/xchu/data/ramlab_dataset zhangkin/lio_sam_6axis /bin/zsh # in the container catkin build source devel/setup.zsh # with dataset download and linked ==> please see more usage in previous section roslaunch lio_sam_6axis ouster128_indoors.launch # 对于在内地的同学，可以换源`dockerhub`后，直接拉取： docker pull zhangkin/lio_sam_6axis ``` ## Documentation The documentation for LIO_SAM_6AXIS can be found in the `doc` directory of the repository. It includes instructions on how to adapt the code for your own sensors and lidars. - [Bilibili](https://www.bilibili.com/video/BV1YS4y1i7nX/) - [Youtube](https://youtu.be/TgKSeNLkExc) ## Dataset and Adaptation LIO_SAM_6AXIS is compatible with a range of datasets and sensor setups. To help you get started, we have included a table that lists some of the datasets and sensors that have been tested with LIO_SAM_6AXIS. | Dataset | Description | Sensors | Download Links | Ground Truth | Comments | | ------------------------------------------------------------ | ------------------------------------------------------------ |
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:a371e34124e8abca, topic:slam, readme:slam