LaMa is a C++11 software library for robotic localization and mapping developed at the Intelligent Robotics and Systems (IRIS) Laboratory at the University of Aveiro - Portugal. It includes a framework for 3D volumetric grids (for mapping), a localization algorithm based on scan matching, and two SLAM solutions (an Online SLAM and a Particle Filter SLAM). The main feature is efficiency. Low computational effort and low memory usage whenever possible. The minimum viable computer to run our localization and SLAM solutions is a Raspberry Pi 3 Model B+. We provide a fast scan-matching approach to mobile robot localization supported by a continuous likelihood field. It can be used to provide accurate localization for robots equipped with a laser and a not-so-good odometry. Nevertheless, good odometry is always recommended.
Features
- To build LaMa, clone it from GitHub and use CMake to build
- Documentation available
- Its only dependency is Eigen3
- Integration with ROS
- Sparse-Dense Mapping (SDM)
- Localization based on Scan Matching
- Online SLAM
Project Samples
