Book Image

Learning Robotics using Python - Second Edition

By : Lentin Joseph
Book Image

Learning Robotics using Python - Second Edition

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)

Working with SLAM using ROS and Kinect

The main aim of deploying vision sensors in our robot is to detect objects and navigate the robot through an environment. SLAM is a algorithm that is used in mobile robots to build up a map of an unknown environment or update a map within a known environment by tracking the current location of the robot.

Maps are used to plan the robot's trajectory and to navigate through this path. Using maps, the robot will get an idea about the environment. The two main challenges in mobile robot navigation are mapping and localization.

Mapping involves generating a profile of obstacles around the robot. Through mapping, the robot will understand what the world looks like. Localization is the process of estimating the position of the robot relative to the map we build.

SLAM fetches data from different sensors and uses it to build maps. The 2D/3D vision...