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

---

[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

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