Robot arms (21 Ergebnisse)

Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

hardcover. Zustand: Fine copy in fine dust jacket. 1st. 8vo, 341 pp. Illus. with photos (illustrator).

Zustand: Very Good. Very Good condition.

Taschenbuch. Zustand: Neu. Neuware - Master the fundamentals of industrial robot arm programming, control systems, motion planning, and AI-powered robotic automation.Industrial robots are transforming manufacturing, logistics, inspection, and automation. However, controlling a robotic manipulator requires more than sending movement commands. Engineers must understand robot structure, coordinate systems, programming logic, feedback control, sensors, motion planning, and safe deployment practices.Robotic Manipulator Control provides a practical pathway for learning how modern industrial robot arms are programmed, controlled, and integrated into real-world automation systems.This beginner-friendly guide takes you from the foundations of robot manipulators to complete robotic workcell development. You will learn how robot commands move from software applications through controllers and motors to precise physical actions.Inside this book, you will learn how to: - Understand industrial robot arm designs, joints, links, axes, payload, reach, accuracy, and repeatability- Plan safe robotic workcells and identify industrial automation hazards- Understand robot controllers, servo systems, encoders, sensors, and communication networks- Work with joint space, Cartesian coordinates, poses, and robot frames- Set up a robotics programming environment using Python and simulation tools- Create Python programs that send robot commands and monitor robot status- Understand forward and inverse kinematics for robotic manipulators- Apply feedback control principles and tune PID controllers- Generate smooth robot trajectories and collision-free movements- Control grippers, tools, and industrial end effectors- Use sensors and force control for accurate robot interaction- Build vision-guided robotic manipulation systems- Create robot applications using ROS 2 and MoveIt 2- Apply artificial intelligence techniques for object recognition and intelligent automation- Design and deploy complete robotic workcellsThe book combines engineering concepts with practical programming approaches. Examples use Python for readable robotics applications, while ROS 2 and MoveIt 2 are introduced for modern robot software development, motion planning, and simulation workflows.You will gradually build the knowledge required to move from simple robot programs to reliable industrial automation systems. Each concept is connected to practical tasks, including simulation testing, hardware integration, safety considerations, and real-world deployment.Whether you are a robotics student, automation engineer, programmer, researcher, technician, or enthusiast entering industrial robotics, this book provides a structured foundation for understanding and developing robotic manipulation systems.Learn how industrial robot arms think, move, interact, and perform complex automation tasks with precision.…

Zustand: New. In English.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This is the first book to focus on solving cooperative control problems of multiple robot arms using different centralized or distributed neural network models, presenting methods and algorithms together with the corresponding theoretical analysis and simulated examples. It is intended for graduate students and academic and industrial researchers in the field of control, robotics, neural networks, simulation and modelling.…

Paperback. Zustand: Brand New. 92 pages. 9.00x6.00x0.25 inches. In Stock.

Zustand: New.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Zustand: Neu. Neural Networks for Cooperative Control of Multiple Robot Arms | Shuai Li (u. a.) | Taschenbuch | xv | Englisch | 2017 | Springer Nature Singapore | EAN 9789811070365 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Zustand: New. In English.

Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book investigates a biologically inspired method of robot arm control, developed with the objective of synthesising human-like motion dynamically, using nonlinear, robust and adaptive control techniques in practical robot systems. The control method caters to a rising interest in humanoid robots and the need for appropriate control schemes to match these systems. Unlike the classic kinematic schemes used in industrial manipulators, the dynamic approachesproposed here promote human-like motion with better exploitation of the robot's physical structure. This also benefits human-robot interaction.The control schemes proposed in this book are inspired by a wealth of human-motion literature that indicates the drivers of motion to be dynamic, model-based and optimal. Such considerations lend themselves nicely to achievement via nonlinear control techniques without the necessity for extensive and complex biological models.The operational-space method of robot control forms the basis of many of the techniques investigated in this book. The method includes attractive features such as the decoupling of motion into task and posture components. Various developments are made in each of these elements. Simple cost functions inspired by biomechanical 'effort' and 'discomfort' generate realistic posture motion. Sliding-mode techniques overcome robustness shortcomings for practical implementation. Arm compliance is achieved via a method of model-free adaptive control that also deals with actuator saturation via anti-windup compensation. A neural-network-centered learning-by-observation scheme generates new task motions, based on motion-capture data recorded from human volunteers. In other parts of the book, motion capture is used to test theories of human movement. All developed controllers are applied to the reaching motion of a humanoid robot arm and are demonstrated to be practically realisable.This book is designed to be of interest to those wishing to achieve dynamics-based human-like robot-arm motion in academic research, advanced study or certain industrial environments. The book provides motivations, extensive reviews, research results and detailed explanations. It is not only suited to practising control engineers, but also applicable for general roboticists who wish to develop control systems expertise in this area.…

Zustand: New. In English.

Gebunden. Zustand: New. &Uumlber den AutorSHUAI LI, PhD, is Assistant Professor in the Department of Computing at the Hong Kong Polytechnic University. LONG JIN, PhD, is Postdoctoral Fellow in the Department of Computing at the Hong Kong .

Zustand: New. 2019. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Neuware - Presents pioneering and comprehensive work on engaging movement in robotic arms, with a specific focus on neural networks This book presents and investigates different methods and schemes for the control of robotic arms whilst exploring the field from all angles. On a more specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations. Kinematic Control of Redundant Robot Arms Using Neural Networks is divided into three parts: Neural Networks for Serial Robot Arm Control; Neural Networks for Parallel Robot Control; and Neural Networks for Cooperative Control. The book starts by covering zeroing neural networks for control, and follows up with chapters on adaptive dynamic programming neural networks for control; projection neural networks for robot arm control; and neural learning and control co-design for robot arm control. Next, it looks at robust neural controller design for robot arm control and teaches readers how to use neural networks to avoid robot singularity. It then instructs on neural network based Stewart platform control and neural network based learning and control co-design for Stewart platform control. The book finishes with a section on zeroing neural networks for robot arm motion generation. - Provides comprehensive understanding on robot arm control aided with neural networks - Presents neural network-based control techniques for single robot arms, parallel robot arms (Stewart platforms), and cooperative robot arms - Provides a comparison of, and the advantages of, using neural networks for control purposes rather than traditional control based methods - Includes simulation and modelling tasks (e.g., MATLAB) for onward application for research and engineering development By focusing on robot arm control aided by neural networks whilst examining central topics surrounding the field, Kinematic Control of Redundant Robot Arms Using Neural Networks is an excellent book for graduate students and academic and industrial researchers studying neural dynamics, neural networks, analog and digital circuits, mechatronics, and mechanical engineering.…

Softcover. Zustand: gut. 2023. Design, Fabrication and Control of Wheeled Upper Body Humanoid Robot with Redundant Arms In deutscher Sprache. pages.

Taschenbuch. Zustand: Neu. Neuware - Build autonomous robots that can navigate, see, plan, and manipulate with ROS 2.ROS 2 Intelligent Robot Projects is a practical, project-driven guide to building intelligent robotic systems with Python, Gazebo, Nav2, OpenCV, MoveIt 2, ros2_control, SLAM, and deep learning.Instead of learning ROS 2 through disconnected examples, you will build one connected robotics stack that progresses from core communication and simulation to autonomous navigation, AI vision, robotic manipulation, and real-hardware deployment.Inside the book, you will learn how to: - Build ROS 2 nodes, topics, services, actions, launch files, and parameters- Model and simulate a mobile robot with URDF, Xacro, Gazebo, and RViz- Control robot motion with ros2_control- Build maps and localize with SLAM- Configure autonomous navigation with Nav2- Process camera data and track objects with OpenCV- Run deep-learning object detection for robot perception- Build and control robotic arms with MoveIt 2- Create collision-aware pick-and-place workflows- Integrate navigation, vision, and manipulation into an intelligent warehouse robot- Troubleshoot TF, sensors, controllers, AI pipelines, and hardware- Move safely from simulation to real ROS 2 hardwareThe book uses ROS 2 Jazzy Jalisco on Ubuntu 24.04 LTS as its primary reference environment and supports a simulation-first workflow, so you can complete the major projects without owning a physical robot.Whether you are a student, Python developer, robotics hobbyist, AI engineer, researcher, or ROS 1 user moving to ROS 2, this book gives you a structured path from your first ROS 2 system to a complete intelligent robot.Go beyond ROS 2 tutorials and start building robots that can map, navigate, see, decide, grasp, and operate as complete autonomous systems.…