Learning Robotics Using Python

Packt Publishing Ltd
2
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If you are an engineer, a researcher, or a hobbyist, and you are interested in robotics and want to build your own robot, this book is for you. Readers are assumed to be new to robotics but should have experience with Python.
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About the author

Lentin Joseph is an electronics engineer, robotics enthusiast, machine vision expert, embedded programmer, and the founder and CEO of Qbotics Labs (http://www.qboticslabs.com) in India. He got his bachelor's degree in electronics and communication engineering at the Federal Institute of Science and Technology (FISAT), Kerala. In his final year engineering project, he created a social robot, which can interact with people. The project was a huge success and got mentioned in visual and print media. The main feature of this robot was that it could communicate with people and reply intelligently. It also has some image-processing capabilities, such as face, motion, and color detection. The entire project was implemented using the Python programming language. His interest in robotics, image processing, and Python began this project. After graduation, he worked at a start-up company based on robotics and image processing for 3 years. In the meantime, he learned famous robotic software platforms—such as Robot Operating system (ROS), V-REP, and Actin (a robotic simulation tool)—and image processing libraries, such as OpenCV, OpenNI, and PCL. He also knows about robot 3D designing, embedded programming on Arduino, and Stellaris Launchpad. After 3 years of work experience, he started a new company called Qbotics Labs, which is mainly focused on research to build great products in domains such as wearable technology, robotics, machine vision, green technology, and online education. He maintains a personal website (http://www.lentinjoseph.com) and a technology blog called technolabsz (http://www.technolabsz.com). He publishes his works on his tech blog. He was a speaker at PyCon2013 India, and he spoke on the topic of learning robotics using Python.
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Additional Information

Publisher
Packt Publishing Ltd
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Published on
May 27, 2015
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Pages
330
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ISBN
9781783287543
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Language
English
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Genres
Computers / Desktop Applications / Design & Graphics
Computers / General
Computers / Machine Theory
Computers / Programming Languages / Python
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Content Protection
This content is DRM free.
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Available on Android devices
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Build a variety of awesome robots that can see, sense, move, and do a lot more using the powerful Robot Operating SystemAbout This BookCreate and program cool robotic projects using powerful ROS librariesWork through concrete examples that will help you build your own robotic systems of varying complexity levelsThis book provides relevant and fun-filled examples so you can make your own robots that can run and workWho This Book Is For

This book is for robotic enthusiasts and researchers who would like to build robot applications using ROS. If you are looking to explore advanced ROS features in your projects, then this book is for you. Basic knowledge of ROS, GNU/Linux, and programming concepts is assumed.

What You Will LearnCreate your own self-driving car using ROSBuild an intelligent robotic application using deep learning and ROSMaster 3D object recognitionControl a robot using virtual reality and ROSBuild your own AI chatter-bot using ROSGet to know all about the autonomous navigation of robots using ROSUnderstand face detection and tracking using ROSGet to grips with teleoperating robots using hand gesturesBuild ROS-based applications using Matlab and AndroidBuild interactive applications using TurtleBotIn Detail

Robot Operating System is one of the most widely used software frameworks for robotic research and for companies to model, simulate, and prototype robots. Applying your knowledge of ROS to actual robotics is much more difficult than people realize, but this title will give you what you need to create your own robotics in no time!

This book is packed with over 14 ROS robotics projects that can be prototyped without requiring a lot of hardware. The book starts with an introduction of ROS and its installation procedure. After discussing the basics, you'll be taken through great projects, such as building a self-driving car, an autonomous mobile robot, and image recognition using deep learning and ROS. You can find ROS robotics applications for beginner, intermediate, and expert levels inside!

This book will be the perfect companion for a robotics enthusiast who really wants to do something big in the field.

Style and approach

This book is packed with fun-filled, end-to-end projects on mobile, armed, and flying robots, and describes the ROS implementation and execution of these models.

Design, build and simulate complex robots using Robot Operating System and master its out-of-the-box functionalitiesAbout This BookDevelop complex robotic applications using ROS for interfacing robot manipulators and mobile robots with the help of high end robotic sensorsGain insights into autonomous navigation in mobile robot and motion planning in robot manipulatorsDiscover the best practices and troubleshooting solutions everyone needs when working on ROSWho This Book Is For

If you are a robotics enthusiast or researcher who wants to learn more about building robot applications using ROS, this book is for you. In order to learn from this book, you should have a basic knowledge of ROS, GNU/Linux, and C++ programming concepts. The book will also be good for programmers who want to explore the advanced features of ROS.

What You Will LearnCreate a robot model of a Seven-DOF robotic arm and a differential wheeled mobile robotWork with motion planning of a Seven-DOF arm using MoveIt!Implement autonomous navigation in differential drive robots using SLAM and AMCL packages in ROSDig deep into the ROS Pluginlib, ROS nodelets, and Gazebo pluginsInterface I/O boards such as Arduino, Robot sensors, and High end actuators with ROSSimulation and motion planning of ABB and Universal arm using ROS IndustrialExplore the ROS framework using its latest versionIn Detail

The area of robotics is gaining huge momentum among corporate people, researchers, hobbyists, and students. The major challenge in robotics is its controlling software. The Robot Operating System (ROS) is a modular software platform to develop generic robotic applications.

This book discusses the advanced concepts in robotics and how to program using ROS. It starts with deep overview of the ROS framework, which will give you a clear idea of how ROS really works. During the course of the book, you will learn how to build models of complex robots, and simulate and interface the robot using the ROS MoveIt motion planning library and ROS navigation stacks.

After discussing robot manipulation and navigation in robots, you will get to grips with the interfacing I/O boards, sensors, and actuators of ROS. One of the essential ingredients of robots are vision sensors, and an entire chapter is dedicated to the vision sensor, its interfacing in ROS, and its programming.

You will discuss the hardware interfacing and simulation of complex robot to ROS and ROS Industrial (Package used for interfacing industrial robots).

Finally, you will get to know the best practices to follow when programming using ROS.

Style and approach

This is a simplified guide to help you learn and master advanced topics in ROS using hands-on examples.

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsAbout This BookLeverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasetsWho This Book Is For

If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.

What You Will LearnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataIn Detail

Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.

Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.

Style and approach

Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

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