Hands-On ROS for Robotics Programming : Program highly autonomous and AI-capable mobile robots powered by ROS
Language: English
Published by Packt Publishing, 2020
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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£ 85.72
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nach der Bestellung gedruckt Neuware - Printed after ordering - Take your ROS skills to the next level by implementing complex robot structures in a ROS simulationKey Features:- Learn fundamental ROS concepts and apply them to solve navigation tasks- Work with single board computers to program smart behavior in mobile robots- Understand how specific characteristics of the physical environment influence your robot's performanceBook Description:Connecting a physical robot to a robot simulation using the Robot Operating System (ROS) infrastructure is one of the most common challenges faced by ROS engineers. With this book, you'll learn how to simulate a robot in a virtual environment and achieve desired behavior in equivalent real-world scenarios.This book starts with an introduction to GoPiGo3 and the sensors and actuators with which it is equipped. You'll then work with GoPiGo3's digital twin by creating a 3D model from scratch and running a simulation in ROS using Gazebo. Next, the book will show you how to use GoPiGo3 to build and run an autonomous mobile robot that is aware of its surroundings. Finally, you'll find out how a robot can learn tasks that have not been programmed in the code but are acquired by observing its environment. You'll even cover topics such as deep learning and reinforcement learning.By the end of this robot programming book, you'll be well-versed with the basics of building specific-purpose applications in robotics and developing highly intelligent autonomous robots from scratch.What You Will Learn:- Get to grips with developing environment-aware robots- Gain insights into how your robots will react in physical environments- Break down a desired behavior into a chain of robot actions- Relate data from sensors with context to produce adaptive responses- Apply reinforcement learning to allow your robot to learn by trial and error- Implement deep learning to enable your robot to recognize its surroundingsWho this book is for:If you are an engineer looking to build AI-powered robots using the ROS framework, this book is for you. Robotics enthusiasts and hobbyists who want to develop their own ROS robotics projects will also find this book useful. Knowledge of Python and/or C++ programming and familiarity with single board computers such as Raspberry Pi is necessary to get the most out of this book.Table of Contents- Assembling the Robot- Unit testing of GoPiGo3- Getting started with ROS- Creating the virtual two wheeled ROS robot- Simulating the robot behavior in a virtual environment with Gazebo- Programming in ROS: Commands and tools - Robot control and simulation - Virtual SLAM and navigation using Gazebo - SLAM for robot navigation- Applying Machine Learning in Robotics - Machine Learning with OpenAI Gym on ROS- Achieve a goal through Reinforcement Learning.…
Seller Inventory # 9781838551308
- Title
- Hands-On ROS for Robotics Programming : Program highly autonomous and AI-capable mobile robots powered by ROS
- Author
- Bernardo Ronquillo Japón
- Publisher
- Packt Publishing
- Publication year
- 2020
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1838551301
- ISBN 13
- 9781838551308
- Item weight
- 802 grams
- Dimensions
- 235x191x24 mm
Take your ROS skills to the next level by implementing complex robot structures in a ROS simulation
Key Features
- Learn fundamental ROS concepts and apply them to solve navigation tasks
- Work with single board computers to program smart behavior in mobile robots
- Understand how specific characteristics of the physical environment influence your robot’s performance
Book Description
Connecting a physical robot to a robot simulation using the Robot Operating System (ROS) infrastructure is one of the most common challenges faced by ROS engineers. With this book, you'll learn how to simulate a robot in a virtual environment and achieve desired behavior in equivalent real-world scenarios.
This book starts with an introduction to GoPiGo3 and the sensors and actuators with which it is equipped. You'll then work with GoPiGo3's digital twin by creating a 3D model from scratch and running a simulation in ROS using Gazebo. Next, the book will show you how to use GoPiGo3 to build and run an autonomous mobile robot that is aware of its surroundings. Finally, you'll find out how a robot can learn tasks that have not been programmed in the code but are acquired by observing its environment. You'll even cover topics such as deep learning and reinforcement learning.
By the end of this robot programming book, you'll be well-versed with the basics of building specific-purpose applications in robotics and developing highly intelligent autonomous robots from scratch.
What you will learn
- Get to grips with developing environment-aware robots
- Gain insights into how your robots will react in physical environments
- Break down a desired behavior into a chain of robot actions
- Relate data from sensors with context to produce adaptive responses
- Apply reinforcement learning to allow your robot to learn by trial and error
- Implement deep learning to enable your robot to recognize its surroundings
Who this book is for
If you are an engineer looking to build AI-powered robots using the ROS framework, this book is for you. Robotics enthusiasts and hobbyists who want to develop their own ROS robotics projects will also find this book useful. Knowledge of Python and/or C++ programming and familiarity with single board computers such as Raspberry Pi is necessary to get the most out of this book.
Table of Contents
- Assembling the Robot
- Unit testing of GoPiGo3
- Getting started with ROS
- Creating the virtual two wheeled ROS robot
- Simulating the robot behavior in a virtual environment with Gazebo
- Programming in ROS: Commands and tools
- Robot control and simulation
- Virtual SLAM and navigation using Gazebo
- SLAM for robot navigation
- Applying Machine Learning in Robotics
- Machine Learning with OpenAI Gym on ROS
- Achieve a goal through Reinforcement Learning
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
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