Git Product home page Git Product logo

knut0815 / aws-deepracer-mapping-sample-project Goto Github PK

View Code? Open in Web Editor NEW

This project forked from aws-deepracer/aws-deepracer-mapping-sample-project

0.0 0.0 0.0 8.38 MB

In this project, use the AWS DeepRacer car to draw a map with SLAM (Simultaneous Localization and Mapping), a technique for creating a map of an environment by estimating a device’s current location as it moves through a space.

License: Apache License 2.0

aws-deepracer-mapping-sample-project's Introduction

Mapping with ROS Noetic on Ubuntu 20.04

Overview

The Mapping sample project provides instructions for using the AWS DeepRacer and Intel RealSense™ D435 along with other open source tools to build a map of your surrounding using SLAM (Simultaneous Localization and Mapping).

License

The source code is released under Apache 2.0.

Setup

Prerequisites

The DeepRacer device comes with all the pre-requisite packages and libraries installed for running the DeepRacer core application. More details about pre installed set of packages and libraries on the DeepRacer, and installing required build systems can be found in the Getting Started section of the AWS DeepRacer Opensource page. The Mapping sample project requires the AWS DeepRacer application to be installed on the device as it leverages the manual drive feature to control the car manually.

Intel RealSense™ D435 / D435i

Connect and mount the Intel RealSense D435 or Intel RealSense D435i to the AWS DeepRacer device. The Intel RealSense cameras provides depth sensor and other required capabilities to collect information from your surrounding.

ROS Noetic on AWS DeepRacer device

Open up a terminal and install ROS Noetic as a root user by following the steps here - http://wiki.ros.org/noetic/Installation/Ubuntu

Download and install other components

Open up a terminal and run the following commands as root user on the AWS DeepRacer device:

  • Set up ROS Noetic environment - After installing ROS Noetic on your AWS DeepRacer, source the setup script for ROS Noetic

          source /opt/ros/noetic/setup.bash
    
  • Install the software packages required to create the map:

    • realsense2_camera:

        export ROS_VER=noetic
        sudo apt-get install ros-$ROS_VER-realsense2-camera
        sudo apt-get install ros-$ROS_VER-realsense2-description
      
    • imu_filter_madgwick:

        sudo apt-get install ros-$ROS_VER-imu-filter-madgwick
      
    • rtabmap_ros:

        sudo apt-get install ros-$ROS_VER-rtabmap-ros
      
    • robot_localization:

        sudo apt-get install ros-$ROS_VER-robot-localization
      

Usage

  • Open up a terminal and run the following commands as root user on the AWS DeepRacer device:

      source /opt/ros/noetic/setup.bash
    
  • Trigger the opensource tracking launch script provided by Intel RealSense:

      roslaunch realsense2_camera opensource_tracking.launch
    
  • Open up another terminal and launch rviz by running the following command as root user:

      source /opt/ros/noetic/setup.bash
      rosrun rviz rviz
    
  • Personalize, collect and visualize the point cloud data by following the steps here.

  • Move the AWS DeepRacer car slowly around the room in Manual mode using the device console.

Sample Demo:

RVIZ when mapping the room by navigating the AWS DeepRacer car:

mapping

Resources

aws-deepracer-mapping-sample-project's People

Contributors

amazon-auto avatar pratik-nichat avatar siddalingesha-ds avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.