Duck Dynasty stars Al and Lisa Robertson were desperate for their love to survive—and with God’s help, they realized the only answer to marital and family betrayal is all-consuming, life-altering, desperate forgiveness. In their new book, they share this message with anyone who wants to exchange broken relationships for healing. The Robertsons know what they’re talking about: They have lived through the pain of adultery and lack of communication in their marriage. And thanks to the healing they’ve experienced, they now help other couples find their own path to forgiveness. This former pastor of 22 years and his wife want you to arrive at a place where you, too, can give and receive forgiveness and find the beauty of reconciliation. By sharing true stories from friends and family, as well as biblical examples, Desperate Forgiveness provides the support you’ll need on the hard road to forgiveness. You’ll learn about the necessity and power of humility; the freedom found in letting go of bitterness; and the restoration and reclamation on the other side of desperation. Al and Lisa Robertson are living proof that choosing and living out forgiveness is worth the effort. Let Desperate Forgiveness show you the way to a changed life and revitalized marriage.

In this comprehensive textbook about robot grasping, readers will discover an integrated look at the major concepts and technical results in robot grasp mechanics. A large body of prior research, including key theories, graphical techniques, and insights on robot hand designs, is organized into a systematic review, using common notation and a common analytical framework. With introductory and advanced chapters that support senior undergraduate and graduate level robotics courses, this book provides a full introduction to robot grasping principles that are needed to model and analyze multi-finger robot grasps, and serves as a valuable reference for robotics students, researchers, and practicing robot engineers. Each chapter contains many worked-out examples, exercises with full solutions, and figures that highlight new concepts and help the reader master the use of the theories and equations presented.

In this paper, we present a deciding technique for robotic dexterous hand configurations. This algorithm can be used to decide on how to configure a robotic hand so it can grasp objects in different scenarios. Receiving as input, several sensor signals that provide information on the object’s shape, the DSmT decision-making algorithm passes the information through several steps before deciding what hand configuration should be used for a certain object and task.

The simple task of grasping objects has been studied for centuries by scientists, therapists and engineers who have tried to understand and duplicate the versatility of the human hand. Using an interdisciplinary approach and new framework for looking at prehension, the authors uncover the subleties of the amazing interaction between the hand and the brain. They draw from such diverse fields as experimental psychology, kinesiology, robotics, neural networks, artificial intelligence, neuropsychology and rehabilitation. A triangle strategy is presented, starting from conceptual models that suggest both experimental and computational models. Chapters describe the multiple postures established by the hand, phases in the dynamic process of reaching for, grasping and manipulating various objects, and the constraints acting on such activity.Appendices provide the complete anatomy of the upper limb, the basics of computational modelling, and the fundamentals of prosthetic and dextrous robot hands. The ultimate goal of this book is to develop a common vocabularly for multidisciplinary researchers who strive to understand a system as complex as the hand under the control of the human brain.

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This book constitutes the refereed proceedings of the First Robotic Grasping and Manipulation Challenge, RGMC 2016, held at IROS 2016, Daejeon, South Korea, in October 2016.The 13 revised full papers presented were carefully reviewed and are describing the rules, results, competitor systems and future directions of the inaugural competition. The competition was designed to allow researchers focused on the application of robot systems to compare the performance of hand designs as well as autonomous grasping and manipulation solutions across a common set of tasks. The competition was comprised of three tracks that included hand-in-hand grasping, fully autonomous grasping, and simulation.

How do we learn? And how can we learn better? In this groundbreaking look at the science of learning, Sanjay Sarma, head of Open Learning at MIT, shows how we can harness this knowledge to discover our true potential. Drawing from his own experience as an educator as well as the work of researchers and innovators at MIT and beyond, in Grasp, Sarma explores the history of modern education, tracing the way in which traditional classroom methods—lecture, homework, test, repeat—became the norm and showing why things needs to change. The book takes readers across multiple frontiers, from fundamental neuroscience to cognitive psychology and beyond, as it considers the future of learning. It introduces scientists who study forgetting, exposing it not as a simple failure of memory but as a critical weapon in our learning arsenal. It examines the role curiosity plays in promoting a state of “readiness to learn” in the brain (and its troublesome twin, “unreadiness to learn”). And it reveals how such ideas are being put into practice in the real world, such as at unorthodox new programs like Ad Astra, located on the SpaceX campus. Along the way, Grasp debunks long-held views such as the noxious idea of “learning styles,” equipping readers with practical tools for absorbing and retaining information across a lifetime of learning.