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github ethz asl bievr lio bievr lio robust lidar inertial odometry through bump image enhanced voxel maps rss 2026 github skip to content navigation menu toggle navigation sign in appearance settings platform ai code creation github copilot write better code with ai github copilot app direct agents from issue to merge mcp registry new integrate external tools developer workflows actions automate any workflow codespaces instant dev environments issues plan and track work code review manage code changes application security github advanced security find and fix vulnerabilities code security secure your code as you build secret protection stop leaks before they start explore why github documentation blog changelog marketplace view all features solutions by company size enterprises small and medium teams startups nonprofits by use case app modernization devsecops devops ci cd view all use cases by industry healthcare financial services manufacturing government view all industries view all 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feedback saved searches use saved searches to filter your results more quickly name query to see all available qualifiers see our documentation cancel create saved search sign in sign up appearance settings resetting focus you signed in with another tab or window reload to refresh your session you signed out in another tab or window reload to refresh your session you switched accounts on another tab or window reload to refresh your session dismiss alert message uh oh there was an error while loading please reload this page ethz asl bievr lio public notifications you must be signed in to change notification settings fork 23 star 177 code issues 1 pull requests 0 actions projects security and quality 0 insights additional navigation options code issues pull requests actions projects security and quality insights ethz asl bievr lio main branches tags go to file code open more actions menu folders and files name name last commit message last commit date latest commit history 22 commits 22 commits github workflows github workflows bievr bievr config config doc doc docker docker interfaces interfaces license license readme md readme md view all files repository files navigation readme bsd 3 clause license more items bievr lio robust lidar inertial odometry through bump image enhanced voxel maps bievr lio is a robust lidar inertial odometry framework that uses a high resolution voxel wise oriented height image map to exploit subtle geometric variations in challenging information sparse environments abstract reliable odometry is essential for mobile robots as they increasingly enter more challenging environments which often contain little information to constrain point cloud registration resulting in degraded lidar inertial odometry lio accuracy or even divergence to address this we present bievr lio a novel approach designed specifically to exploit subtle variations in the available geometry for improved robustness we propose a high resolution map representation that stores surfaces as voxel wise oriented height images this representation can directly be used for registration without the calculation of intermediate geometric primitives while still supporting efficient updates since informative geometry is often sparsely distributed in the environment we further propose a map informed point sampling strategy to focus registration on geometrically informative regions improving robustness in uninformative environments while reducing computational cost compared to global high resolution sampling experiments across multiple sensors platforms and environments demonstrate state of the art performance in well constrained scenes and substantial improvements in challenging scenarios where baseline methods diverge additionally we demonstrate that the fine grained geometry captured by bievr lio can be used for downstream tasks such as elevation mapping for robot locomotion setup the core estimator bievr_lio is a self contained ros independent library on top of it we provide both a ros1 interface bievr_lio_ros and a ros2 interface bievr_lio_ros2 which live side by side under interfaces installation dependencies bievr lio is intentionally light on dependencies the core estimator only needs eigen and ceres build instructions for both ros versions are below each also offers an optional docker image for quickly trying out the system without setting up dependencies ros1 for quick testing docker if you just want to try the system out without setting up dependencies build the image and drop into a shell inside it cd docker run_docker_ros1 sh b the b flag builds the image on subsequent runs you can omit it to reuse the existing image your data folder is mounted to home bievr data inside the container so you can keep datasets outside the image to open another terminal inside the running container e g to launch a node and play a bag docker exec it bievr lio ros1 bin bash build requires ros noetic and python3 catkin tools sudo apt install python3 catkin tools create a catkin workspace and clone bievr lio into it mkdir p catkin_ws src cd catkin_ws catkin init catkin config extend opt ros noetic catkin config cmake args dcmake_build_type release catkin config merge devel cd catkin_ws src git clone git github com ethz asl bievr lio git bievr lio install the ceres version used by bievr lio with the provided script builds ceres 2 2 0 from source bievr lio docker scripts install_ceres sh optional livox support the livox custommsg branches are only compiled if the corresponding driver is found in the workspace at build time otherwise bievr lio builds fine without them if you need to process livox data clone and build the matching driver into catkin_ws src before building bievr lio each driver also needs its livox sdk installed system wide livox gen1 livox_ros_driver enables bievr_with_livox livox_ros_driver livox sdk livox gen2 livox_ros_driver2 enables bievr_with_livox2 livox_ros_driver2 livox sdk2 build and source it cd catkin_ws catkin build bievr_lio_ros source devel setup bash ros2 for quick testing docker if you just want to try the system out without setting up dependencies build the image and drop into a shell inside it cd docker run_docker_ros2 sh b the b flag builds the image on subsequent runs you can omit it to reuse the existing image your data folder is mounted to home bievr data inside the container to open another terminal inside the running container e g to launch a node and play a bag docker exec it bievr lio ros2 bin bash build requires ros2 jazzy and python3 colcon common extensions sudo apt install python3 colcon common extensions the system was tested on jazzy but other ros2 distributions might also work create a colcon workspace and clone bievr lio into it mkdir p colcon_ws src cd colcon_ws src git clone git github com ethz asl bievr lio git bievr lio install the ceres version used by bievr lio with the provided script builds ceres 2 2 0 from source bievr lio docker scripts install_ceres sh optional livox support the livox custommsg branch is only compiled if livox_ros_driver2 is found in the workspace at build time otherwise bievr lio builds fine without it if you need to process livox data clone and build the driver into colcon_ws src before building bievr lio it also needs its livox sdk2 installed system wide only gen2 exists for ros2 enables bievr_with_livox livox_ros_driver2 livox sdk2 build and source it from the workspace root so colcon picks up both bievr the core and interfaces ros2 cd colcon_ws source opt ros jazzy setup bash colcon build packages up to bievr_lio_ros2 source install setup bash run data bievr lio provides two entry points available for both ros versions process_topics runs online it subscribes to the lidar and imu topics and processes messages as they arrive use it with a live sensor or alongside rosbag play process_bag reads a recorded bag directly and pushes its messages through the pipeline as fast as they can be processed no real time playback this is the preferred choice for offline evaluation and reproducing results in the commands below replace sensor_config with one of the provided configs see configuration or your own add rviz true to bring up the visualization ros1 process live topics roslaunch bievr_lio_ros process_topics launch sensor_config sensor_config replay a rosbag roslaunch bievr_lio_ros process_bag launch sensor_config sensor_config rosbag path to bag bag ros2 process live topics ros2 launch bievr_lio_ros2 process_topics launch py sensor_config sensor_config replay a rosbag2 directory ros2 launch bievr_lio_ros2 process_bag launch py sensor_config sensor_config rosbag path to bag_dir configuration the configuration is split in two files config params yaml algorithm parameters map resolution sampling optimization imu window these are dataset independent and typically do not need to be adjusted the defaults have been validated across a wide range of sensors platforms and environments config sensor_configs name yaml per dataset per sensor settings the lidar and imu topic names the lidar imu extrinsic calibration and the lidar min max range select a sensor config at launch with sensor_config name which resolves to config sensor_configs name yaml an absolute path starting with is used verbatim so configs may also live outside the package likewise params name default params selects config name yaml provided datasets we provide ready to use sensor configs for the following public datasets config dataset enwide enwide ncd newer college dataset gamma geode mars mars lvig grandtour grandtour running on your own data to run bievr lio on a new sensor or dataset copy one of the provided sensor configs to config sensor_configs your_name yaml and adjust topics pointcloud topics imu the topic names in your data calibration the t_imu_lidar extrinsic lidar imu rotation and translation for your setup lidar min_range_m lidar max_range_m the usable range of your lidar the algorithm parameters in params yaml can usually be left at their defaults acknowledgements we thank the authors of dlio wavemap and ugpm for open sourcing their works that served as an inspiration for us we used ascii image converter for our ascii art citation please cite our work if you are using bievr lio in your research article pfreundschuh2026bievr title bievr lio robust lidar inertial odometry through bump image enhanced voxel maps author pfreundschuh patrick and tuna turcan and le gentil cedric and siegwart roland and cadena cesar and oleynikova helen year 2026 journal robotics science and systems about bievr lio robust lidar inertial odometry through bump image enhanced voxel maps rss 2026 patripfr github io bievr lio resources readme license bsd 3 clause license uh oh there was an error while loading please reload this page activity custom properties stars 177 stars watchers 5 watching forks 23 forks report repository releases 1 v1 0 0 latest jul 3 2026 packages 0 uh oh there was an 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