Generate top down image from gazebo world

This tutorial describes the process of creating a building using the Building Editor.

Open the Building Editor

1. Make sure Gazebo is installed.

2. Start up gazebo.

3. On the menu, proceed to , or hit to open the editor.

Graphical user interface

The editor is composed of the following 3 areas:

1. The Palette, where you can choose features and materials for your building.

2. The 2D View, where you can import a floor plan to mark over (optional) and insert walls, windows, doors and stairs.

3. The 3D View, where you can spot a preview of your building. It is also where you can assign colors and textures to different parts of your building.

You may create a scene from scratch, or use an existing image as a template to trace over. This image can be, for example, a 2D laser scan of a building.

Click here to get an example floor plan, then proceed as follows:

1. Click on the button. The dialog will come up.

2. Step 1: Choose the image you previously saved on your laptop and click .

3. Step 2: To make sure the walls you trace over the image arrive up in the correct scale, you must set the image's resolution in pixels per meter (). If we knew the reso

   gazebo Docker official image overview

   Quick reference

   Supported tags and respective links

   No supported tags

   Quick reference (cont.)

   What is Gazebo⁠?

   Robot simulation is an essential tool in every roboticist's toolbox. A well-designed simulator makes it doable to rapidly test algorithms, style robots, and perform regression testing using realistic scenarios. Gazebo proposals the ability to accurately and efficiently simulate populations of robots in complex indoor and outdoor environments. At your fingertips is a robust physics engine, high-quality graphics, and convenient programmatic interfaces. Best of all, Gazebo is free with a vibrant community.

   How to use this image

   Create a in your Gazebo project

   You can then build and run the Docker image:

   Deployment use cases

   This dockerized image of Gazebo is intended to provide a simplified and consistent platform to build and deploy cloud based robotic simulations. Built from the official Ubuntu image and Gazebo's official Debian packages, it includes recent supported releases for quick access and download. This provides roboticists in research and industry with an easy way to develop continuous integration and testing

   Initially, you are going to include some kind of a topo map:

   Note that if you are going to follow step2 below (using Google maps), you will still need to do some post processing of what you got, there is no way to do it in a fully automated way. I would prefer to create my have landscape, rather than using Google maps. Probably, a compromise remedy is to use "real" blueprint with topo lines as a layer in an image editor, draw your own topo guide on top, and then dispose the map layer.

   Then you need to turn this chart into a colored one, so that each color represents the height. You can do it by hand (like I did), or you can follow a greate guide here

   Here is the (scaled down to fit this page) result:

   Next step will be to turn it all into a point cloud, by moving the "topo-lines" up or down, according to their color:

   Then we need to do some extrapolation, adding points in between:

   Now as we have a kind surface, all we need to do (in a perfect world) is to turn it into a mesh. Unfortunately, we are not living in a pefrect world, and meshes created by libraries like o3d, pymesh, trimesh and so on, are either plain wrong or not waterproof (contain holes).

   So the next step (in
   
   

   # Gazebo Simulation

   Gazebo(opens new window) is a powerful 3D simulation environment for autonomous robots that is particularly suitable for testing object-avoidance and computer vision. This page describes its use with SITL and a single vehicle. Gazebo can also be used with HITL and for multi-vehicle simulation.

   Supported Vehicles: Quad (Iris and Solo, Hex (Typhoon H480), Generic quad delta VTOL, Tailsitter, Plane, Rover, Submarine/UUV.

   WARNING

   Gazebo is often used with ROS, a toolkit/offboard API for automating vehicle control. If you plan to use PX4 with ROS you should follow theROS Instructions to install both ROS and Gazebo (and thereby evade installation conflicts).

   (opens new window)

   Note

   See Simulation for general information about simulators, the simulation environment, and simulation configuration (e.g. supported vehicles).

   # Installation

   Gazebo 9 setup is included in our standard build instructions:

   Additional installation instructions can be found on gazebosim.org(opens new window).

   # Running the Simulation

   Run a simulation by starting PX4 SITL and gazebo with the airframe configuration to load (multicopters, planes, VTOL, optical flow and mul

   ROS Depth Camera Integration

   Introduction

   In this tutorial, you'll learn how to connect a Gazebo depth camera to ROS. The tutorial consists of 3 main steps:

   1. Create a Gazebo model that includes a ROS depth camera plugin
   2. Set up the depth camera in Gazebo
   3. View the depth camera's output in RViz.

   This is a self-contained tutorial; it does not use the RRBot that is developed in other Gazebo ROS tutorials. It is designed to help you get up and running quickly using computer vision in ROS and Gazebo.

   Prerequisites

   You should install gazebo_ros_pkgs before doing this tutorial.

   Create a Gazebo Model with a Depth Camera Plugin

   Because Gazebo and ROS are separate projects that do not depend on each other, sensors from the repository (such as depth cameras) do not include ROS plugins by default. This means you have to make a custom camera based on those in the Gazebo model repository, and then add your own tag to make the depth camera data publish point clouds and images to ROS topics.

   You should choose a depth camera to use from those available in Gazebo. This tutorial will use the Microsoft Kinect, but the procedure should be the same for other depth cameras on the lis