Электронная библиотека Финансового университета

     
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Japon, Bernardo Ronquillo. Hands-on ROSs for robotics programming: a practical guide to programming highly autonomous robots with ROS / Bernardo Ronquillo Japon. — 1 online resource — <URL:http://elib.fa.ru/ebsco/2381024.pdf>.

Дата создания записи: 14.02.2020

Тематика: Robots — Programming.

Коллекции: EBSCO

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Оглавление

  • Title Page
  • Copyright and Credits
  • About Packt
  • Contributors
  • Table of Contents
  • Preface
  • Section 1: Physical Robot Assembly and Testing
  • Chapter 1: Assembling the Robot
    • Understanding the GoPiGo3 robot
      • The robotics perspective
      • The programming perspective
      • Robot kit and resources
    • Getting familiar with the embedded hardware
      • The GoPiGo3 board 
      • Raspberry Pi 3B+
      • Why does a robot need a CPU?
    • Deep diving into the electromechanics
      • The most useful sensors
        • Distance sensor
        • Line follower
        • IMU sensor
        • Pi Camera
    • Putting it all together
    • Quick hardware test
      • Resources
      • Getting started with DexterOS
      • Coding with Bloxter
      • Calibrating the robot
      • Driving the robot
      • Checking the sensors
      • Shutting down the robot
    • Summary
    • Questions
    • Further reading
  • Chapter 2: Unit Testing of GoPiGo3
    • Technical requirements
    • Getting started with Python and JupyterLab
      • Launching JupyterLab for GoPiGo3
      • Hardware testing
        • Testing battery, LEDs, and motors/encoders
          • Battery level
          • Hardware information and current voltage levels
          • LEDs and blinkers
          • Motors and encoders test
    • Unit testing of sensors and drives
      • Quick start with sensors and motors
      • Driving around
      • Distance sensor
        • Check port connections
        • Distance sensor unit test
          • GoPiGo3 API library
          • DI sensors API library
      • Servo package
        • Servo package unit test
      • Line follower
        • Line follower unit test
      • Inertial Measurement Unit (IMU)
        • IMU unit test
      • Raspberry Pi
        • Pi unit test
      • GoPiGo3 projects
    • Summary
    • Questions
    • Further reading
  • Chapter 3: Getting Started with ROS
    • Technical requirements
    • ROS basic concepts
      • The ROS graph
      • roscore
      • Workspaces and catkin
    • Configuring your ROS development environment
      • Installing ROS
        • Ubuntu and ROS in the Raspberry Pi
      • Integrated Development Environment (IDE)
        • Installing RoboWare Studio
    • Communication between ROS nodes – messages and topics
      • Creating a workspace
        • Creating a workspace and building it using RoboWare
      • Setting up the ROS package
        • Accessing package files and building the workspace using RoboWare
      • A node publishing a topic
      • A node that listens to the topic
      • Combining the publisher and subscriber in the same node
    • Using publicly available packages for ROS
    • Summary
    • Questions
    • Further reading
  • Section 2: Robot Simulation with Gazebo
  • Chapter 4: Creating the Virtual Two-Wheeled ROS Robot
    • Technical requirements
    • Getting started with RViz for robot visualization
    • Building a differential drive robot with URDF
      • Overview of URDF for GoPiGo3
      • URDF robot body
        • Caster
      • The URDF model's left and right wheels
    • Inspecting the GoPiGo3 model in ROS with RViz
      • Understanding the roslaunch command
        • Using Roboware to execute a launch file
      • Controlling the GoPiGo3 robot's wheels from RViz
        • Using the joint_state_publisher package
    • Robot frames of reference in the URDF model
    • Using RViz to check the model while building
      • Changing the aspect of the model in the RViz window
      • Helpful ROS tools for checking purposes
    • Summary
    • Questions
    • Further reading
  • Chapter 5: Simulating Robot Behavior with Gazebo
    • Technical requirements
    • Getting started with the Gazebo simulator
    • Making modifications to the robot URDF
      • Extending URDF to produce an SDF robot definition
      • Collisions and physical properties
      • Gazebo tags
    • Verifying a Gazebo model and viewing the URDF
      • Launching the GoPiGo model in Gazebo
        • Explaining configurable launch files using the tag
    • Moving your model around
      • Guidelines for tuning the Gazebo model
    • Summary
    • Questions
    • Further reading
  • Section 3: Autonomous Navigation Using SLAM
  • Chapter 6: Programming in ROS - Commands and Tools
    • Technical requirements
    • Setting up a physical robot
      • Downloading and setting up Ubuntu Mate 18.04 
      • Access customization
        • Updating your system and installing basic utilities
        • Enabling SSH access
      • Setting up a VNC server (x11vnc)
        • Setting up autostart on boot
        • Forcing the HDMI output and screen layout
      • The Geany IDE
      • Installing drivers for the GoPiGo3 and DI Sensors
      • Setting up the Pi Camera
      • Installing ROS Melodic
        • Installing a Pi Camera ROS package
    • A quick introduction to ROS programming
      • Setting up the workspace
      • Cloning a ROS package
      • Our first execution of a ROS node
    • Case study 1 – writing a ROS distance-sensor package
      • Creating a new package
      • Producing your source code
        • Including the required libraries – rospy and msgs.msg 
        • Assigning a node name to the script
        • Defining the publisher
        • Setting up the msg_range object
        • Changing units to the International System of Units
        • Adding a measured distance and timestamp to the msg_range object
        • Setting the reading frequency
        • Running an infinite loop
        • Publishing each new event
        • Waiting until the next reading
        • Launching the ROS execution environment
    • Working with ROS commands
      • Shell commands
        • Changing the current location
        • Listing files and folders inside a package
        • Editing any file inside a package
      • Execution commands
        • The central process of the ROS environment
        • Executing a single node
      • Information commands
        • Exploring topics
        • Exploring nodes
        • The rosmsg command
        • The rosbag command
      • Packages and the catkin workspace
    • Creating and running publisher and subscriber nodes
    • Automating the execution of nodes using roslaunch
    • Case study 2 – ROS GUI development tools – the Pi Camera 
      • Analyzing the ROS graph using rqt_graph
      • Displaying image data using rqt_image_view
      • Graphing time series of sensor data with rqt_plot
      • Playing a recorded ROS session with rqt_bag 
        • Distance sensor
        • The Pi Camera
    • Customizing robot features using ROS parameters
    • Summary
    • Questions
    • Further reading
  • Chapter 7: Robot Control and Simulation
    • Technical requirements
    • Setting up the GoPiGo3 development environment
      • ROS networking between the robot and the remote computer
        • Communication between ROS environments
          • Robot network configuration
          • Laptop network configuration
        • Launching the master node and connecting
    • Case study 3 – remote control using the keyboard
      • Running the gopigo3 node in the robot
        • Inspecting published topics and messages
      • Teleoperation package
      • Running teleoperation on a laptop
        • Teleoperation with the mouse
    • Remote control using ROS topics
      • The motion control topic – /cmd_vel
      • Using /cmd_vel to directly drive GoPiGo3
      • Checking the X, Y, and Z axes of GoPiGo3
      • Composing motions
    • Remotely controlling both physical and virtual robots
      • Reverting the ROS master to the local computer
      • Simulating GoPiGo3 with Gazebo
        • Adding the controller to the Gazebo model of the robot
      • Real-world and simulation at once
    • Summary
    • Questions
    • Further reading
  • Chapter 8: Virtual SLAM and Navigation Using Gazebo
    • Technical requirements
      • ROS navigation packages
      • ROS master running on the local computer
    • Dynamic simulation using Gazebo
      • Adding sensors to the GoPiGo3 model
        • Camera model
          • Simulating the camera
        • Distance sensor
          • Simulating the distance sensor
    • Components in navigation
      • Costmaps for safe navigation
    • Robot perception and SLAM
      • Adding a Laser Distance Sensor (LDS)
        • Simulating the LDS
      • SLAM concepts
        • Occupancy Grid Map (OGM)
        • The SLAM process
        • The navigation process
    • Practising SLAM and navigation with the GoPiGo3
      • Exploring the environment to build a map using SLAM
      • Driving along a planned trajectory using navigation
    • Summary
    • Questions
    • Further reading
  • Chapter 9: SLAM for Robot Navigation
    • Technical requirements
      • Setting the ROS master to be in the robot
    • Preparing an LDS for your robot
      • Setting up YDLIDAR
        • Integrating with the remote PC
        • Running the YDLIDAR ROS package
      • Integrating with Raspberry Pi
        • Checking that YDLIDAR works with GoPiGo3
        • Visualizing scan data in the Raspberry Pi desktop
        • Grouping launch files
        • Visualizing scan data from the remote laptop
      • Processing YDLIDAR data from a remote laptop
    • Creating a navigation application in ROS
    • Practicing navigation with GoPiGo3
      • Building a map of the environment
      • Navigating GoPiGo3 in the real world
    • Summary
    • Questions
    • Further reading
  • Section 4: Adaptive Robot Behavior Using Machine Learning
  • Chapter 10: Applying Machine Learning in Robotics
    • Technical requirements
    • Setting up the system for TensorFlow
      • Installing pip
        • Installing the latest version
      • Installing TensorFlow and other dependencies
      • Achieving better performance using the GPU
    • ML comes to robotics
      • Core concepts in ML
        • Selecting features in ML
      • The ML pipeline
    • From ML to deep learning
      • ML algorithms
        • Regression
        • Logistic regression
        • Product recommendation
        • Clustering
        • Deep learning
      • Deep learning and neural networks
        • The input layer
        • The hidden layer(s)
        • The output layer
    • A methodology to programmatically apply ML in robotics
      • A general approach to application programming
      • Integrating an ML task
    • Deep learning applied to robotics – computer vision
      • Object recognition in Gazebo
      • Object recognition in the real world
    • Summary
    • Questions
    • Further reading
  • Chapter 11: Machine Learning with OpenAI Gym
    • Technical requirements
    • An introduction to OpenAI Gym
      • Installing OpenAI Gym
        • Without Anaconda (optional)
        • Installing gym in development mode (optional)
      • Installing OpenAI ROS
      • Agents, artificial intelligence, and machine learning
      • The cart pole example
        • Environments
        • Spaces
        • Observations
        • Running the full cart pole example
      • Q-learning explained – the self-driving cab example
        • How to run the code for the self-driving cab
        • Reward table
        • Action space
        • State space
        • Self-driving cab example using the RL algorithm
        • Evaluating the agent
        • Hyperparameters and optimization
    • Running an environment
    • Configuring the environment file
    • Running the simulation and plotting the results
      • Checking your progress with the logger
    • Summary
    • Questions
    • Further reading
  • Chapter 12: Achieve a Goal through Reinforcement Learning
    • Technical requirements
    • Preparing the environment with TensorFlow, Keras, and Anaconda
      • TensorFlow backend
      • Deep learning with Keras
      • ROS dependency packages
    • Understanding the ROS Machine Learning packages
      • Training scenarios
      • ROS package structure for running a reinforcement learning task
    • Setting the training task parameters
    • Training GoPiGo3 to reach a target location while avoiding obstacles
      • How to run the simulations
      • Scenario 1 – travel to a target location
      • Scenario 2 – travel to a target location avoiding the obstacles
        • Testing the trained model
    • Summary
    • Questions
    • Further reading
  • Assessment
    • Chapter 1: Assembling the Robot
    • Chapter 2: Unit Testing of GoPiGo3
    • Chapter 3: Getting Started with ROS
    • Chapter 4: Creating the Virtual Two-Wheeled ROS Robot
    • Chapter 5: Simulating Robot Behavior with Gazebo
    • Chapter 6: Programming in ROS - Commands and Tools
    • Chapter 7: Robot Control and Simulation
    • Chapter 8: Virtual SLAM and Navigation Using Gazebo
    • Chapter 9: SLAM for Robot Navigation
    • Chapter 10: Applying Machine Learning in Robotics
    • Chapter 11: Machine Learning with OpenAI Gym
    • Chapter 12: Achieve a Goal through Reinforcement Learning
  • Other Books You May Enjoy
  • Index

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