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The Gazebo Learning Project shares the history and philosophy of Gazebo Park School and the core philosophic principles of this pedagogy including a unique view of the child and role of the teacher, a model for nature and outdoor education, the use of Gestalt practice with children and adults, and the benefits of pure play.
Build exciting robotics projects such as mobile manipulators, self-driving cars, and industrial robots powered by ROS, machine learning, and virtual reality Key FeaturesCreate and program cool robotic projects using powerful ROS librariesBuild industrial robots like mobile manipulators to handle complex tasksLearn how reinforcement learning and deep learning are used with ROSBook Description 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. What you will learnGrasp the basics of ROS and understand ROS applicationsUncover how ROS-2 is different from ROS-1Handle complex robot tasks using state machinesCommunicate with multiple robots and collaborate to build apps with themExplore ROS capabilities with the latest embedded boards such as Tinker Board S and Jetson NanoDiscover how machine learning and deep learning techniques are used with ROSBuild a self-driving car powered by ROSTeleoperate your robot using Leap Motion and a VR headsetWho this book is for If you’re a student, hobbyist, professional, or anyone with a passion for learning robotics and interested in learning about algorithms, motion control, and perception capabilities from scratch, this book is for you. This book is also ideal for anyone who wants to build a new product and for researchers to make the most of what’s already available to create something new and innovative in the field of robotics.
Build a variety of awesome robots that can see, sense, move, and do a lot more using the powerful Robot Operating System About This Book Create and program cool robotic projects using powerful ROS libraries Work through concrete examples that will help you build your own robotic systems of varying complexity levels This book provides relevant and fun-filled examples so you can make your own robots that can run and work Who 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 Learn Create your own self-driving car using ROS Build an intelligent robotic application using deep learning and ROS Master 3D object recognition Control a robot using virtual reality and ROS Build your own AI chatter-bot using ROS Get to know all about the autonomous navigation of robots using ROS Understand face detection and tracking using ROS Get to grips with teleoperating robots using hand gestures Build ROS-based applications using Matlab and Android Build interactive applications using TurtleBot In 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.
Gestalt Therapy: History, Theory, and Practice is an introductory text, written by major Gestalt theorists, that will engage those new to Gestalt therapy. Editors Ansel Woldt and Sarah M. Toman introduce the historical underpinnings and fundamental concepts of Gestalt therapy and illustrate applications of those concepts to therapeutic practice. The book is unique in that it is the first Gestalt text specifically designed for the academic and training institute settings. Gestalt Therapy takes both a conceptual and a practical approach to examining classic and cutting-edge constructs.
As the first book to explore the confluence of three emerging yet critical fields of study, this work sets an exacting standard. The editors’ aim was to produce the most authoritative guide for ecojustice, place-based education, and indigenous knowledge in education. Aimed at a wide audience that includes, but is not restricted to, science educators and policymakers, Cultural Studies and Environmentalism starts from the premise that schooling is a small part of the larger educational domain in which we live and learn. Informed by this overarching notion, the book opens up ways in which home-grown talents, narratives, and knowledge can be developed, and eco-region awareness and global relationships can be facilitated. Incorporating a diversity of perspectives that include photography, poetry and visual art, the work provides a nuanced lens for evaluating educational problems and community conditions while protecting and conserving the most threatened and vulnerable narratives. Editors and contributors share the view that the impending loss of these narratives should be discussed much more widely than is currently the case, and that both teachers and children can take on some of the responsibility for their preservation. The relevance of ecojustice to this process is clear. Ecojustice philosophy is a way of learning about how we frame, or perceive, the world around us—and why that matters. Although it is not synonymous with social or environmental justice, the priorities of ecojustice span the globe in the same way. It incorporates a deep recognition of the appropriateness and significance of learning from place-based experiences and indigenous knowledge systems rather than depending on some urgent “ecological crises” to advocate for school and societal change. With a multiplicity of diverse voices coming together to explore its key themes, this book is an important starting point for educators in many arenas. It brings into better focus a vital role for the Earth’s ecosystems in the context of ecosociocultural theory and participatory democracy alike. “Encompassing theoretical, empirical, and experiential standpoints concerning place-based knowledge systems, this unique book argues for a transformation of (science) education’s intellectual tradition of thinking that emphasizes individual cognition. In its place, the book offers a wisdom tradition of thinking, living, and being that emphasizes community survival in harmony within itself and with Mother Earth.” Glen Aikenhead
This proceedings volume showcases the latest achievements in research and development in Educational Robotics presented at the 7th International Conference on Robotics in Education (RiE) held in Vienna, Austria, during April 14-15, 2016. The book offers a range of methodologies for teaching robotics and presents various educational robotics curricula. It includes dedicated chapters for the design and analysis of learning environments as well as evaluation means for measuring the impact of robotics on the students’ learning success. Moreover, the book presents interesting programming approaches as well as new applications, the latest tools, systems and components for using robotics. The presented applications cover the whole educative range, from elementary school to high school, college, university and beyond, for continuing education and possibly outreach and workforce development. The book provides a framework involving two complementary kinds of contributions: on the one hand on technical aspects and on the other hand on matters of didactic.
In the evolving environment of education, academic scholars face the daunting challenge of navigating a multitude of pedagogical approaches and technologies. The design of effective learning activities demands a nuanced understanding of didactic innovation, instructional design, and the integration of technology. As educators strive to meet the diverse needs of learners, the demand for innovative solutions to enhance teaching methodologies becomes more pressing than ever. Technological Tools for Innovative Teaching emerges as a comprehensive solution to the challenges educators encounter in the modern academic arena. The book unravels the intricacies of pedagogical scenarios, providing a step-by-step guide to designing learning activities that align with educational objectives. By addressing topics such as the pedagogy of error, flipped classroom strategies, and tech pedagogy, the book equips scholars with a diverse toolkit to revolutionize their teaching methods.
Build cutting edge machine and deep learning systems for the lab, production, and mobile devices Key FeaturesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesImplement graph neural networks, transformers using Hugging Face and TensorFlow Hub, and joint and contrastive learningLearn cutting-edge machine and deep learning techniquesBook Description Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments. This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natural language processing (NLP), and graph neural networks (GNNs)), covers working example apps, and then dives into TF in production, TF mobile, and TensorFlow with AutoML. What you will learnLearn how to use the popular GNNs with TensorFlow to carry out graph mining tasksDiscover the world of transformers, from pretraining to fine-tuning to evaluating themApply self-supervised learning to natural language processing, computer vision, and audio signal processingCombine probabilistic and deep learning models using TensorFlow ProbabilityTrain your models on the cloud and put TF to work in real environmentsBuild machine learning and deep learning systems with TensorFlow 2.x and the Keras APIWho this book is for This hands-on machine learning book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow, and AutoML to build machine learning systems. Some machine learning knowledge would be useful. We don't assume TF knowledge.
This book addresses many applications of artificial intelligence in robotics, namely AI using visual and motional input. Robotic technology has made significant contributions to daily living, industrial uses, and medicinal applications. Machine learning, in particular, is critical for intelligent robots or unmanned/autonomous systems such as UAVs, UGVs, UUVs, cooperative robots, and so on. Humans are distinguished from animals by capacities such as receiving visual information, adjusting to uncertain circumstances, and making decisions to take action in a complex system. Significant progress has been made in robotics toward human-like intelligence; yet, there are still numerous unresolved issues. Deep learning, reinforcement learning, real-time learning, swarm intelligence, and other developing approaches such as tiny-ML have been developed in recent decades and used in robotics. Artificial intelligence is being integrated into robots in order to develop advanced robotics capable of performing multiple tasks and learning new things with a better perception of the environment, allowing robots to perform critical tasks with human-like vision to detect or recognize various objects. Intelligent robots have been successfully constructed using machine learning and deep learning AI technology. Robotics performance is improving as higher quality, and more precise machine learning processes are used to train computer vision models to recognize different things and carry out operations correctly with the desired outcome. We believe that the increasing demands and challenges offered by real-world robotic applications encourage academic research in both artificial intelligence and robotics. The goal of this book is to bring together scientists, specialists, and engineers from around the world to present and share their most recent research findings and new ideas on artificial intelligence in robotics.