Wyatt Newman is a professor in the department of Electrical Engineering and Computer Science at Case Western Reserve University, where he has taught since 1988. His research is in the areas of mechatronics, robotics and computational intelligence, in which he has 12 patents and over 150 technical publications. He received the S.B. degree from Harvard College in Engineering Science, the S.M. degree in Mechanical Engineering from M.I.T. in thermal and fluid sciences, the M.S.E.E. degree from Columbia University in control theory and network theory, and the Ph.D. degree in Mechanical Engineering from M.I.T. in design and control. A former NSF Young Investigator in robotics, Prof. Newman has also held appointments as: a senior member of research staff, Philips Laboratories; visiting scientist at Philips Natuurkundig Laboratorium; visiting faculty at Sandia National Laboratories, Intelligent Systems and Robotics Center; NASA summer faculty fellow at NASA Glenn Research Center; visiting fellow in neuroscience at Princeton University; distinguished visiting fellow at Edinburgh University, School of Informatics, and the Hung Hing Ying Distinguished Visiting Professor at the University of Hong Kong. Prof. Newman led robotics teams competing in the 2007 DARPA Urban Challenge and in the 2015 DARPA Robotics Challenge, and he continues to be interested in wide-ranging aspects and applications of robotics.
A Systematic Approach to Learning Robot Programming with ROS provides a comprehensive, introduction to the essential components of ROS through detailed explanations of simple code examples along with the corresponding theory of operation. The book explores the organization of ROS, how to understand ROS packages, how to use ROS tools, how to incorporate existing ROS packages into new applications, and how to develop new packages for robotics and automation. It also facilitates continuing education by preparing the reader to better understand the existing on-line documentation.
The book is organized into six parts. It begins with an introduction to ROS foundations, including writing ROS nodes and ROS tools. Messages, Classes, and Servers are also covered. The second part of the book features simulation and visualization with ROS, including coordinate transforms.
The next part of the book discusses perceptual processing in ROS. It includes coverage of using cameras in ROS, depth imaging and point clouds, and point cloud processing. Mobile robot control and navigation in ROS is featured in the fourth part of the book
The fifth section of the book contains coverage of robot arms in ROS. This section explores robot arm kinematics, arm motion planning, arm control with the Baxter Simulator, and an object-grabber package. The last part of the book focuses on system integration and higher-level control, including perception-based and mobile manipulation.
This accessible text includes examples throughout and C++ code examples are also provided at https://github.com/wsnewman/learning_ros
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Teaches ROS from the ground up without dependence on detailed prior expertiseIntroduces the reader to ROS incrementally, building on a coherent sequence of topicsAssumes rudimentary knowledge of C++, but does not assume expertise in details of programming, robotics, machine vision, kinematics/dynamics, or software engineeringPresents ROS programming together with Gazebo simulationsProvides a survey of robotics topics, including kinematics, machine vision, point-cloud processing, mapping, navigation, and user interfacesAccess PowerPoint slides for the textbook here: https://www.teacherspayteachers.com/Store/Learn-Ros-And-Robotics-Systematically
ROS FOUNDATIONS. Introduction to ROS: ROS tools and nodes. Messages, Classes and Servers. SIMULATION AND VISUALIZATION IN ROS. Simulation in ROS. Coordinate Transforms in ROS. Sensing and Visualization in ROS. PERCEPTUAL PROCESSING IN ROS. Using Cameras in ROS. Depth Imaging and Point Clouds. Point Cloud Processing. MOBILE ROBOTS IN ROS. Mobile-Robot. Motion Control. Mobile-Robot Navigation. ROBOT ARMS IN ROS. Low-Level Control. Robot Arm Kinematics. Arm Motion Planning. Arm Control with the Baxter Simulator. An Object-Grabber Package. SYSTEM INTEGRATION AND HIGHER-LEVEL CONTROL. Perception-Based Manipulation. Mobile Manipulation
ROS is becoming the de facto means of robot programming, and is expected to be crucial for robotics development in self-driving cars, service robots, and more. This book provides a comprehensive introduction to the essential components of ROS through detailed explanations of simple code examples along with the corresponding theory of operation.
A Systematic Approach to Learning Robot Programming with ROS provides a comprehensive, introduction to the essential components of ROS through detailed explanations of simple code examples along with the corresponding theory of operation. The book explores the organization of ROS, how to understand ROS packages, how to use ROS tools, how to incorporate existing ROS packages into new applications, and how to develop new packages for robotics and automation. It also facilitates continuing education by preparing the reader to better understand the existing on-line documentation.
The book is organized into six parts. It begins with an introduction to ROS foundations, including writing ROS nodes and ROS tools. Messages, Classes, and Servers are also covered. The second part of the book features simulation and visualization with ROS, including coordinate transforms.
The next part of the book discusses perceptual processing in ROS. It includes coverage of using cameras in ROS, depth imaging and point clouds, and point cloud processing. Mobile robot control and navigation in ROS is featured in the fourth part of the book
The fifth section of the book contains coverage of robot arms in ROS. This section explores robot arm kinematics, arm motion planning, arm control with the Baxter Simulator, and an object-grabber package. The last part of the book focuses on system integration and higher-level control, including perception-based and mobile manipulation.
This accessible text includes examples throughout and C++ code examples are also provided at https://github.com/wsnewman/learning_ros
SECTION I ROS FOUNDATIONSnIntroduction to ROS: ROS tools and nodesnSome Ros Concepts nWriting Ros Nodes nSome More Ros Tools: Catkin_Simple, Roslaunch, Rqt_Console, And Rosbag nA Minimal Simulator and Controller Example nWrap-Up nMessages, Classes and Servers nDefining Custom Messages nIntroduction to Ros Services nUsing C++ Classes in Ros nCreating Library Modules In Ros nIntroduction to Action Servers and Action ClientsnIntroduction to The Parameter Server nWrap-Up nSECTION II SIMULATION AND VISUALIZATION IN ROSnSimulation in ROS nThe Simple Two-Dimensional Robot Simulator nModeling for Dynamic Simulation nThe Unified Robot Deillegalscription Format nIntroduction to Gazebo nA Minimal Joint Controller nUsing A Gazebo Plug-In for Joint Servo Control nBuilding A Mobile Robot Model nSimulating The Mobile Robot Model nCombining Robot Models nWrap-Up nCoordinate Transforms in ROS nIntroduction to Coordinate Transforms In Ros nThe Transform Listener nUsing The Eigen Library nTransforming Ros Datatypes nWrap-Up nSensing and Visualization in ROS nMarkers And Interactive Markers In Rviz nDisplaying Sensor Values in Rviz nWrap-Up nSECTION IIIPERCEPTUAL PROCESSING IN ROSnUsing Cameras in ROS nProjective Transformation Into Camera CoordinatesnIntrinsic Camera Calibration nIntrinsic Calibration Of Stereo Cameras nUsing Opencv with Ros nWrap-Up nDepth Imaging and Point Clouds nDepth from Scanning Lidar nDepth from Stereo Cameras nDepth Cameras nWrap-Up nPoint Cloud Processing nA Simple Point-Cloud Display Node nLoading and Displaying Point-Cloud Images From Disk nSaving Published Point-Cloud Images to Disk nInterpreting Point-Cloud Images with Pcl MethodsnAn Object Finder nSECTION IV MOBILE ROBOTS IN ROSnMobile-Robot Motion Control nDesired State Generation nRobot State Estimation nDifferential-Drive Steering Algorithms nSteering with Respect to Map Coordinates nWrap-Up nMobile-Robot Navigation nMap Making nPath Planning nAn Example Move-Base Client nModifying The Navigation Stack nWrap-Up nSECTION V ROBOT ARMS IN ROSnLow-Level Control nA One-Dof, Prismatic-Joint Robot Model nAn Example Position Controller nAn Example Velocity Controller nAn Example Force Controller nTrajectory Messages for Robot Arms A Trajectory Interpolation Action Server For A 7-Dof Arm nWrap-Up nRobot Arm Kinematics nForward Kinematics nInverse Kinematics nWrap-Up nArm Motion Planning nCartesian Motion Planning nDynamic Programming for Joint-Space Planning nCartesian-Motion Action Servers nWrap-UpArm Control with the Baxter Simulator nRunning The Baxter Simulator nBaxter Joints and Topics nBaxter's Grippers nHead Pan Control nCommanding Baxter Joints nUsing The Ros Joint Trajectory Controller nJoint-Space Record and Playback Nodes nBaxter Kinematics nBaxter Cartesian Moves nWrap-Up nAn Object-Grabber Package nObject-Grabber Code Organization nAn Object Manipulation Query Service nGeneric Gripper Services nAn Object-Grabber Action Server nAn Example Object-Grabber Action Client nWrap-Up nSECTION VI SYSTEM INTEGRATION AND HIGHER-LEVEL CONTROLnPerception-Based Manipulation nExtrinsic Camera Calibration nIntegrated Perception and Manipulation nMobile Manipulation nMobile Manipulator Model nMobile Manipulation nWrap-Up nConclusion
Wyatt Newman is a professor in the department of Electrical Engineering and Computer Science at Case Western Reserve University, where he has taught since 1988. His research is in the areas of mechatronics, robotics and computational intelligence, in which he has 12 patents and over 150 technical publications. He received the S.B. degree from Harvard College in Engineering Science, the S.M. degree in Mechanical Engineering from M.I.T. in thermal and fluid sciences, the M.S.E.E. degree from Columbia University in control theory and network theory, and the Ph.D. degree in Mechanical Engineering from M.I.T. in design and control. A former NSF Young Investigator in robotics, Prof. Newman has also held appointments as: a senior member of research staff, Philips Laboratories; visiting scientist at Philips Natuurkundig Laboratorium; visiting faculty at Sandia National Laboratories, Intelligent Systems and Robotics Center; NASA summer faculty fellow at NASA Glenn Research Center; visiting fellow in neuroscience at Princeton University; distinguished visiting fellow at Edinburgh University, School of Informatics, and the Hung Hing Ying Distinguished Visiting Professor at the University of Hong Kong. Prof. Newman led robotics teams competing in the 2007 DARPA Urban Challenge and in the 2015 DARPA Robotics Challenge, and he continues to be interested in wide-ranging aspects and applications of robotics.
Klappentext
ROS is becoming the de facto means of robot programming, and is expected to be crucial for robotics development in self-driving cars, service robots, and more. This book provides a comprehensive introduction to the essential components of ROS through detailed explanations of simple code examples along with the corresponding theory of operation.
