RTAB-Map 学习笔记

version: 0.11.13-kinetic

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.

• RTAB-Map Saves the Kidnapped Robot

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[TOC]

概述

RTAB-Map (Real-Time Appearance-Based Mapping) is a RGB-D Graph-Based SLAM approach based on an incremental appearance-based loop closure detector.

The loop closure detector uses a bag-of-words approach to determinate how likely a new image comes from a previous location or a new location. When a loop closure hypothesis is accepted, a new constraint is added to the map’s graph, then a graph optimizer minimizes the errors in the map.

A memory management approach is used to limit the number of locations used for loop closure detection and graph optimization, so that real-time constraints on large-scale environnements are always respected.

RTAB-Map can be used alone with a handheld Kinect or stereo camera for 6DoF RGB-D mapping, or on a robot equipped with a laser rangefinder for 3DoF mapping.

RTAB-Map框架图

Sensors

• Stereo Camera: Bumblebee2, ZED camera, etc.
• RGB-D Camera: Kinect, RealSense, etc.

Front-end

Back-end

Add Key-Frame to Graph

Loop Closure Detection

Graph Optimization

Map(2D/3D) Generation

Demo Robot Mapping

• Command

roslaunch rtabmap_ros demo_robot_mapping.launch rtabmapviz:=false rviz:=true

• Node Graph

demo_robot_mapping_graph

Nodes

/rtabmap/rtabmap

• 流程图

digraph g { rankdir = LR;

subgraph cluster0{
    label="Parameters";
    parameters_;
}

subgraph cluster1{
    label="MapsManager";
    initMaps;
}

subgraph cluster2{
    label="CoreWrapper Nodelet";
    onInit;
    Callback;
}

subgraph cluster3{
    label="RTABMap Corelib";
    initRTABMap;
    process;
}

subgraph cluster4{
    label="Memory";
    newMemory;
    initMemory;
    loadDataFromDb;
}

subgraph cluster5{
    label="DBDriver";
    createDB;
}
subgraph cluster6{
    node [shape=box, size="20,20"];
    {
          Feature2D_create;
          newVWDictionary;
          Registration_create;
          newRegistrationIcp;
          newOccupancyGrid;
    }
}

CoreNode -> onInit [label="nodelet::load()"];

onInit -> parameters_;
onInit -> initMaps;
onInit -> initRTABMap;
onInit -> Callback;

Callback -> process;

initRTABMap -> newMemory;
initRTABMap -> initMemory;

newMemory -> Feature2D_create [lhead=cluster6];

initMemory -> createDB;
initMemory -> loadDataFromDb;

}

/points_xyzrgb

• 流程图

digraph g{ rankdir = LR; rviz -> points_xyzrgb [label="launch nodelet"]; }

Code Analization

CameraModel

\[ FOV_{Horizontal} = \frac{W_{img}/2}{f_x} \]

Problem

• Transform::interpolate