Seirios RNS supports multiple mapping algorithms. Jump to the algorithm of interest here on the right panel (desktop view only) ➡️
The most commonly used mapping algorithm, the cameras mounted on robots populate and generate a map of its surroundings
Users can manually teleoperate the robot, to 'reveal' the map represented by white areas in the map
Incorporating this feature into Seirios allows users to automatically map large areas without manually driving with virtual controls. The auto-mapping feature was originally developed for a wall-scanning construction project
Automatic mapping without manual controls from users
Seirios RNS mapping the environment in 3D
For higher accuracy, range and better visual representation of environmental features, users can opt to map in 3D. A 2D map will be generated from a 3D map too
RTAB-Map (Real-Time Appearance-Based Mapping) is a RGB-D, Stereo and Lidar Graph-Based SLAM approach based on an incremental appearance-based loop closure detector.
RTABMAP is a mapping algorithm which produces the same 2D map with scan
As its namesake, it uses real time images to map the environment
ORB-SLAM is a keyframe and feature-based Monocular SLAM. It operates in real-time in large environments, being able to close loops and perform camera relocalisation from very different viewpoints.
Seirios is able to support mapping with the use of monocular, stereo, and RGB-D cameras. Green 'dots' are features recognised and stored in the map data, generating a 2D map
Intel RealSense D435 - a depth camera that can be used for ORBSLAM camera based mapping