Fusion SLAM
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  • OVERVIEW AND INTRODUCTION
  • INSTALLING
  • DATASETS
  • TUTORIALS FOR ROVIOLI (ONLINE FRONTEND)
  • TUTORIALS FOR USING MAPLAB (OFFLINE TOOLS) - BASICS
  • TUTORIALS FOR USING MAPLAB (OFFLINE TOOLS) - USE-CASES
  • TUTORIALS FOR USING MAPLAB SERVER (ONLINE)
  • HARDWARE INTEGRATION AND SENSOR CALIBRATION
  • TUTORIALS FOR EXTENDING MAPLAB
  • DEVELOPEMENT GUIDELINES
  • ADDITIONAL FORMATS
Project
  • 简体中文
  • English
Home
  • OVERVIEW AND INTRODUCTION
  • INSTALLING
  • DATASETS
  • TUTORIALS FOR ROVIOLI (ONLINE FRONTEND)
  • TUTORIALS FOR USING MAPLAB (OFFLINE TOOLS) - BASICS
  • TUTORIALS FOR USING MAPLAB (OFFLINE TOOLS) - USE-CASES
  • TUTORIALS FOR USING MAPLAB SERVER (ONLINE)
  • HARDWARE INTEGRATION AND SENSOR CALIBRATION
  • TUTORIALS FOR EXTENDING MAPLAB
  • DEVELOPEMENT GUIDELINES
  • ADDITIONAL FORMATS
Project
  • 简体中文
  • English
  • OVERVIEW AND INTRODUCTION

    • Introduction to the Maplab Framework
    • Main Papers
    • Additional Citations
    • Related Research
    • FAQ
    • Known Issues
  • INSTALLING

    • Installing on Ubuntu
    • Compilation and Debugging
  • DATASETS
  • TUTORIALS FOR ROVIOLI (ONLINE FRONTEND)

    • ROVIOLI Introduction
    • Running ROVIOLI in VIO mode: calibartion files, rostopics, bag/topic mode, visualization
    • Running ROVIOLI in Localization mode
    • Multi-session mapping with ROVIOLI
  • TUTORIALS FOR USING MAPLAB (OFFLINE TOOLS) - BASICS

    • Basic Console Usage
    • Parameters (Gflags)
    • Console map management: load, save, basic visualization
    • Inspecting and visualizing a map
    • Map visualization: see your map in RViz!
    • Preparing a single session map: optimization, loop-closure
    • Understanding loop-closure
    • Optimizing VI-Maps
    • Preparing a multi-session map: map anchoring, loop-closure, pose-graph relaxation
    • Dense Reconstruction: attaching resources to map, available reconstruction tools
    • Resource Importer
  • TUTORIALS FOR USING MAPLAB (OFFLINE TOOLS) - USE-CASES

    • Multi-session use case: CLA, multi-floor use-case
    • Map sparsification: make your mapping more efficient
    • Stereo Dense Reconstruction: EuRoC, multi-session reconstruction use-case
    • External Features
  • TUTORIALS FOR USING MAPLAB SERVER (ONLINE)
  • HARDWARE INTEGRATION AND SENSOR CALIBRATION

    • Sensor Calibration Format: ncamera, imu-sigmas
    • Initial sensor calibration with Kalibr
    • Sensor calibration refinement
    • Intel RealSense ZR300
    • VersaVIS
  • TUTORIALS FOR EXTENDING MAPLAB

    • Using the MapManager
    • Using Timing and Statistics
    • /maplab/docs/pages/tutorials-extending-maplab/C_Coding-Examples:-Creating-a-custom-console-plugin.html
    • /maplab/docs/pages/tutorials-extending-maplab/D_Coding-Examples:-Working-with-the-VI-Map.html
    • Console Plugin System
  • DEVELOPEMENT GUIDELINES

    • Importing maplab to Eclipse
    • Contributing to maplab
    • Header Include Guide
    • Debugging applications
    • Expressing frame transformations in code
    • Verbosity Policy
  • ADDITIONAL FORMATS

CSV Dataset Format

It is often useful to interface the visual-inertial maps with other research tools (such as Python scripts, Matlab, deep learning frameworks). A consistent map constructed from multiple recordings and spanning a large area and a timeframe is very valuable for lifelong mapping, place recognition and other experiments. Maplab contains a CSV exporter that outputs the data stored in the map to a an easily readable format that can be universally accessed.

This page describes the output of csv_export command in the maplab console. The command operates per mission and creates a folder named after the mission id in the export path. For each mission, the following data is exported:

Vertices

File name: vertices.csv

ColumnDescriptionUnitFrame
1vertex index--
2timestampns-
3position xmglobal
4position ymglobal
5position zmglobal
6orientation quaternion x-global
7orientation quaternion y-global
8orientation quaternion z-global
9orientation quaternion w-global
10velocity xm/smission
11velocity ym/smission
12velocity zm/smission
13accelerometer bias xm/s^2imu/sensor
14accelerometer bias ym/s^2imu/sensor
15accelerometer bias zm/s^2imu/sensor
16gyroscope bias xrad/simu/sensor
17gyroscope bias yrad/simu/sensor
18gyroscope bias zrad/simu/sensor

IMU data

File name: imu.csv

ColumnDescriptionUnitFrame
1IMU timestampns-
2-7IMU data 1 (6 values)rad/s and m/s^2imu/sensor

Tracks/keypoints

File name: tracks.csv

ColumnDescriptionUnitFrame
1timestampns-
2vertex index--
3frame index--
4keypoint index--
5keypoint measurement 0pxdistorted img
6keypoint measurement 1pxdistorted img
7keypoint measurement uncertainty--
8keypoint scale--
9keypoint track id--

Descriptors

File name: descriptors.csv

ColumnDescriptionUnitFrame
1-Ndescriptor byte as integer--

The rows are ordered the same as in the tracks file.

Landmarks

File name: landmarks.csv

ColumnDescriptionUnitFrame
1landmark index--
2landmark position xmglobal
3landmark position ymglobal
4landmark position zmglobal

Observations

File name: observations.csv

ColumnDescriptionUnitFrame
1vertex index--
2frame index--
3keypoint index--
4landmark index--