BLAM! is an open-source software package for fusing measurements from a wide variety of sensors in real-time for the purpose of 3D mapping and rigid body tracking. This codebase is motivated by the lack of a single universal algorithm for performing Simultaneous Localization and Mapping (SLAM) across any enumeration of input data streams from different sensors. BLAM! is developed by Erik Nelson from the Berkeley AI Research Laboratory (BAIR).
BLAM! supports input sensor data from 2D LiDARS, 3D LiDARS, most cameras, IMUs, GPS devices, INS systems, and RGB-D sensors.
BLAM! is written in C++ with some Python interface elements. Input sensor streams should be provided by the user in Robot Operating System (ROS) format (i.e. in topic form). Currently supported ROS sensor message types include
- 2D LiDAR as a
sensor_msgs/PointCloud2message - 3D LiDAR as a
sensor_msgs/PointCloud2message - IMU messages as a
sensor_msgs/Imumessage - Monocular camera images as a
sensor_msgs/Imagemessage - Stereo camera images as a pair of
sensor_msgs/Imagemessages - RGB-D images as a pair of
sensor_msgs/Imagemessages - GPS as a
???message
This repository contains two ROS workspaces (one internal, one external) that work, so the build process is managed by the update script. To build, first make sure that you do not have any other ROS workspaces in your ROS_PACKAGE_PATH, then clone the repository and from the top directory execute
./update