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    • RNS Features
      • Core
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        • 🗺️Mapping
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        • 1️⃣Pre-installation Checks
          • ✅Software Checks
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            • 🔵(0.5/4) Before Starting Robot Checks
            • 🔵(1/4) Linear Speed Calibration Check
            • 🔵(2/4) Angular Speed Calibration Check
            • 🔵(3/4) Odometry Check
            • 🔵(4/4) Straight-line Check
        • 2️⃣'Easy-deploy' for Seirios
          • Installing docker
          • Installing Seirios RNS
          • Starting Seirios
        • 3️⃣Hardware Integration
        • 4️⃣Navigation Tuning
        • 5️⃣Full Licence Activation
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      • FMS Installation Guide
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      • RNS Plugin Installation Guide
        • Ubuntu
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      • Concepts
        • Map System
        • Tasks
        • Traffic Management
      • Robot Integration Manual
        • Getting Started
        • SDK & Communication Protocols
        • Capabilities
          • Connection
          • Teleoperation
          • Pose
          • LiDAR
          • Emergency Stop
          • Camera
          • Mapping
          • Navigation
          • Localization
          • Queueing
          • Traffic Management
        • Deployment
        • Tutorial: Integrating Robotis Turtlebot3 Simulation
          • 1. Setup Robot Plugin & Establish Connection
          • 2. Integrating Teleoperation
          • 3. Manage the SLAM Node dynamically
          • 4. Integrating the Mapping process
          • 5. Manage the Navigation Node dynamically
          • 6. Integrating the Navigation process
          • 7. Integrating Localization
          • 8. Integrating the Queueing Operations
          • 9. Containerizing the Robot Plugin
    • FAQs
  • Seirios Simple
    • Device Minimum Resolutions
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  • 2D Mapping
  • Auto Mapping 🚩
  • 3D Mapping 🚩
  • RTAB-MAP 🚩
  • ORB-SLAM Camera Based Mapping 🚩

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  1. Seirios RNS
  2. RNS Features
  3. Core

Mapping

PreviousTeleoperationNextTasks

Last updated 7 months ago

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Seirios RNS supports multiple mapping algorithms. Jump to the algorithm of interest here on the right panel (desktop view only) ➡️

Please be informed that all mapping modes (except 2D mapping) are disabled by default as they require special hardware configurations. These include Automatic mapping, 3D mapping, RTAB mapping and ORB-SLAM mapping and are indicated with flags 🚩 below

2D Mapping

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

Auto Mapping 🚩

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

Map does not save automatically once mapping is done. Click 'Stop' to prompt the 'save map' model

3D Mapping 🚩

3D mapping requires a 3D LiDAR and a capable CPU (Intel/AMD x86 recommended)

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 🚩

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.

As its namesake, it uses real time images to map the environment

ORB-SLAM Camera Based Mapping 🚩

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

Substitutable with similar cameras with depth sensing capabilities

🗺️
Seirios RNS mapping the environment in 3D
RTABMAP is a mapping algorithm which produces the same 2D map with scan
Intel RealSense D435 - a depth camera that can be used for ORBSLAM camera based mapping