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Learning Robotics using Python

Learning Robotics using Python

By : Lentin Joseph
3.1 (8)
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Learning Robotics using Python

Learning Robotics using Python

3.1 (8)
By: Lentin Joseph

Overview of this book

Robot Operating System (ROS) is one of the most popular robotics software frameworks in research and industry. It has various features for implementing different capabilities in a robot without implementing them from scratch. This book starts by showing you the fundamentals of ROS so you understand the basics of differential robots. Then, you'll learn about robot modeling and how to design and simulate it using ROS. Moving on, we'll design robot hardware and interfacing actuators. Then, you'll learn to configure and program depth sensors and LIDARs using ROS. Finally, you'll create a GUI for your robot using the Qt framework. By the end of this tutorial, you'll have a clear idea of how to integrate and assemble everything into a robot and how to bundle the software package.
Table of Contents (12 chapters)
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Chapter 4, Simulating a Differential Drive Robot Using ROS

  1. Sensor modeling in Gazebo can be done using Gazebo plugins. The sensor model can be written using C++, which can be plugged in to the Gazebo simulator.
  2. ROS is interfaced to Gazebo using Gazebo ROS plugin. When we load this plugin into Gazebo, we can able to control Gazebo through ROS interface.
  3. The important tags are <inertia>, <collision>, and <gazebo>.
  4. The Gmapping package in ROS is an implementation of Fast SLAM algorithm, which can be used in robot to map the environment and localizing on it. Using Gmapping in ROS is a straightforward process, including the gmapping node with necessary parameters and topics such as odometry and laser scan.
  5. The Move_base node has a provision to handle various navigation subsystem in a robot. It is having a provision to handle global and local planner, also the map...

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