ROS Integration

 

This page describes my research utilizing the Robot Operating System (ROS) software. ROS provides libraries and tools to help software developers create robot applications. It provides hardware abstraction, device drivers, libraries, visualizers, message-passing, package management, and more. Running sets of ROS-based processes are represented in a graph architecture where processing takes place in nodes that may receive, post and multiplex sensor, control, state, planning, actuator and other messages. ROS is completely open source (BSD) and free for others to use, change and commercialize upon.

ROS Gazebo Quadrotor Outdoor World Simulation

Along with ROS, Gazebo is used for simulation. A well-designed simulator makes it possible to rapidly test algorithms, design robots, and perform regression testing using realistic scenarios. Gazebo offers the ability to accurately and efficiently simulate populations of robots in complex indoor and outdoor environments.

ROS RVIZ Quadrotor 2D Navigation Simulation

 

Gazebo includes a robust physics engine, high-quality graphics, and convenient programmatic and graphical interfaces. Also, Gazebo is free with a vibrant community.

ROS RVIZ Quadrotor 3D Navigation Simulation

 

 

4 thoughts on “ROS Integration

  1. Greetings.
    Dear Professor Wil Selby, I am writing to you, hoping not to be inopportune, I am a student of Engineering in Mechatronics, in Ecuador, he has been reading about ROS, it seems to me a very interesting subject as a thesis plan, I am very interested in the drone simulation using Gazebo and ROS (for thesis?), In my search for a topic, I found it on the internet, my question is, you have a broad knowledge on these robotics topics, could advise me or give me some idea of ​​some related thesis topic With the Exposed, in advance thank you very much for any response you could give me and congratulating you for your achievements and continue to reap success.

    1. Diana,

      Thanks for reaching out! Your project sounds exciting. Depending on where you want to focus, I think you could look at different control algorithms like PID or LQR. You could also look at simulating a camera and doing some computer vision. If you wanted to research sensor fusion like Kalman filters, you could simulate IMUs, accelerometers, and GPS. Lastly, simulating a LIDAR sensor can allow you to research mapping, SLAM, obstacle avoidance, and SLAM. My 2D and 3D navigation pages on this site. Let me know if that helps!

  2. Greetings.
    Dear Professor Wil Selby, I am a student of Engineering in computer science, In algeria, i’ve been studying machine learning etc , and i want to work on self driving cars in my bachelor thesis , i’m wondering if you can advice me , and what you think about my project and Ros , is it good simulator? etc
    Thank you so much

    1. I think that’s a great idea. I just developed some simulations using ROS for an autonomous ground vehicle. I used the Udacity Self Driving Car Nanodegree program as a reference to create some simple neural networks. I used TensorFlow and Keras specifically. The code is available here and I am working on writing documentation on how to set it up and use it.

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