SMACH (pronounced as smash) is a Python-based library that helps us handle complex robot behaviors. It is a standalone Python tool that can be used to build hierarchical or concurrent state machines. While its core is ROS-independent, wrappers are written in the smach_ros package (http://wiki.ros.org/smach_ros?distro=melodic) to support integration with ROS systems via actions, services, and topics. SMACH is best useful when you're able to describe robot behaviors and actions more explicitly (like in our waiter robot analogy-state machine diagram). SMACH is a simple and wonderful tool to use and define state machines and is quite powerful when used in combination with ROS actions. The resultant combination can help us build more sophisticated systems. Let's look at some of its concepts in detail to help understand SMACH in more detail.
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ROS Robotics Projects,
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ROS Robotics Projects,
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Overview of this book
Nowadays, heavy industrial robots placed in workcells are being replaced by new age robots called cobots, which don't need workcells. They are used in manufacturing, retail, banks, energy, and healthcare, among other domains. One of the major reasons for this rapid growth in the robotics market is the introduction of an open source robotics framework called the Robot Operating System (ROS).
This book covers projects in the latest ROS distribution, ROS Melodic Morenia with Ubuntu Bionic (18.04). Starting with the fundamentals, this updated edition of ROS Robotics Projects introduces you to ROS-2 and helps you understand how it is different from ROS-1. You'll be able to model and build an industrial mobile manipulator in ROS and simulate it in Gazebo 9. You'll then gain insights into handling complex robot applications using state machines and working with multiple robots at a time. This ROS book also introduces you to new and popular hardware such as Nvidia's Jetson Nano, Asus Tinker Board, and Beaglebone Black, and allows you to explore interfacing with ROS. You'll learn as you build interesting ROS projects such as self-driving cars, making use of deep learning, reinforcement learning, and other key AI concepts.
By the end of the book, you'll have gained the confidence to build interesting and intricate projects with ROS.
Table of Contents (14 chapters)
Preface
Free Chapter
Getting Started with ROS
Introduction to ROS-2 and Its Capabilities
Building an Industrial Mobile Manipulator
Handling Complex Robot Tasks Using State Machines
Building an Industrial Application
Multi-Robot Collaboration
ROS on Embedded Platforms and Their Control
Reinforcement Learning and Robotics
Deep Learning Using ROS and TensorFlow
Creating a Self-Driving Car Using ROS
Teleoperating Robots Using a VR Headset and Leap Motion
Face Detection and Tracking Using ROS, OpenCV, and Dynamixel Servos
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