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Connectionist Robot Motion Planning: A Neurally-Inspired Approach to Visually-Guided Reaching is the third series in a cluster of books on robotics and related areas as part of the Perspectives in Artificial Intelligence Series. This series focuses on an experimental paradigm using the MURPHY system to tackle critical issues surrounding robot motion planning. MURPHY is a robot-camera system developed to explore an approach to the kinematics of sensory-motor learning and control for a multi-link arm. Organized into eight chapters, this book describes the guiding of a multi-link arm to visual targets in a cluttered workspace. It primarily focuses on "ecological solutions that are relevant to the typical visually guided reaching behaviors of humans and animals in natural environments. Algorithms that work well in unmodeled workspaces whose effective layouts can change from moment to moment with movements of the eyes, head, limbs, and body are also presented. This book also examines the strengths of neurally inspired connectionist representations and the utility of heuristic search when good performance, even if suboptimal, is adequate for the task. The co-evolution of MURPHY's design with the brain, presumably in response to similar computational pressures, is described in the concluding chapters, specifically presenting the division of labor between programmed-feedforward and visual-feedback modes of limb control. Design engineers in the fields of biology, neurophysiology, and cognitive psychology will find this book of great value.
One of the ultimate goals in Robotics is to create autonomous robots. Such robots will accept high-level descriptions of tasks and will execute them without further human intervention. The input descriptions will specify what the user wants done rather than how to do it. The robots will be any kind of versatile mechanical device equipped with actuators and sensors under the control of a computing system. Making progress toward autonomous robots is of major practical inter est in a wide variety of application domains including manufacturing, construction, waste management, space exploration, undersea work, as sistance for the disabled, and medical surgery. It is also of great technical interest, especially for Computer Science, because it raises challenging and rich computational issues from which new concepts of broad useful ness are likely to emerge. Developing the technologies necessary for autonomous robots is a formidable undertaking with deep interweaved ramifications in auto mated reasoning, perception and control. It raises many important prob lems. One of them - motion planning - is the central theme of this book. It can be loosely stated as follows: How can a robot decide what motions to perform in order to achieve goal arrangements of physical objects? This capability is eminently necessary since, by definition, a robot accomplishes tasks by moving in the real world. The minimum one would expect from an autonomous robot is the ability to plan its x Preface own motions.
The contributions to this volume, the sixteenth in the prestigious Attention and Performance series, revisit the issue of modularity, the idea that many functions are independently realized in specialized, autonomous modules. Although there is much evidence of modularity in the brain, there is also reason to believe that the outcome of processing, across domains, depends on the synthesis of a wide range of constraining influences. The twenty-four chapters in Attention and Performance XVI look at how these influences are integrated in perception, attention, language comprehension, and motor control. They consider the mechanisms of information integration in the brain; examine the status of the modularity hypothesis in light of efforts to understand how information integration can be successfully achieved; and discuss information integration from the viewpoints of psychophysics, physiology, and computational theory. A Bradford Book. Attention and Performance series.
The book is interdisciplinary and focuses on the topic of artificial consciousness: from neuroscience to artificial intelligence, from bioengineering to robotics. It provides an overview on the current state of the art of research in the field of artificial consciousness and includes extended and revised versions of the papers presented at the International Workshop on ‘Artificial Consciousness', held in November 2005 at Agrigento (Italy).
The Knowledge Level In Expert Systems: Conversations and Commentary deals with artificial intelligence, cognitive science, qualitative models, problem solving architectures, construction of knowledge bases, machine learning integration, knowledge sharing or reusability, and mapping problem-solving methods. The book tackles two opposing dogmas: first, that control is generic so is in the inference engine; and two, deep and surface knowledge are different so deep knowledge belongs in a performance system. The text also explains how to use SPARK, a selection method, in approaching the task features that can be used to select or construct the problem-solving method suitable for the task. An alternative method to SPARK starts with an analysis of the domain model and a classification using primitive inference steps. The book also adds that expert problem solving is a form of qualitative modeling that connects other expert systems and engineering. The text then describes very large knowledge bases, particularly, the volume of which knowledge bases can be integrated with expert systems, coherence maintenance, and use/neutral representation of knowledge. Task analysis and method selection focuses on SPARK; how theories about the relation between task features and expert system solutions can be empirically validated. The book also enumerates the benefits and limitations of a generic task approach, and how various modules with their specific internal architectures can be integrated. Programmers, computer engineers, computer technicians, and computer instructors dealing with many aspects of computers such as programming, networking, engineering or design will find the book highly useful.
The concept of self-organization is at the heart of the theory of complex systems. It describes how order can emerge from disorder in otherwise chaotic nonlinear dynamical systems. This book investigates and surveys the role of self-organization in a wide variety of disciplines. The contributions are written by world-renowned scientists and philosophers at a level that is accessible to nonspecialists.
This text features a broad array of research efforts in computer vision including low level processing, perceptual organization, object recognition and active vision. The volume's nine papers specifically report on topics such as sensor confidence, low level feature extraction schemes, non-parametric multi-scale curve smoothing, integration of geometric and non-geometric attributes for object recognition, design criteria for a four degree-of-freedom robot head, a real-time vision system based on control of visual attention and a behavior-based active eye vision system. The scope of the book provides an excellent sample of current concepts, examples and applications from multiple areas of computer vision.
Advances in Robotic Systems, Part 1 shows how the activity in robotic systems has increased significantly over the past decade. Major centers of research and development in robotic systems were established on the international scene, and these became focal points for the brilliant research efforts of many academicians and industrial professionals. The systems aspects of robotics, in general, and of robot control, in particular, are manifested through a number of technical facts. This book comprises 10 chapters, with the first focusing on applications of neural networks to robotics. The following chapters then discuss a unified approach to kinematic modeling, identification and compensation for robot calibration; nonlinear control algorithms in robotic systems; and kinematic and dynamic task space motion planning for robot control. Other chapters cover discrete kinematic modeling techniques in Cartesian space for robotic system; force distribution algorithms for multifingered grippers; frequency analysis for a discrete-time robot system; minimum cost trajectory planning for industrial robots; tactile sensing techniques in robotic systems; and sensor data fusion in robotic systems. This book will be of interest to practitioners in the fields of computer science, systems science, and mathematics.
In this book, new results or developments from different research backgrounds and application fields are put together to provide a wide and useful viewpoint on these headed research problems mentioned above, focused on the motion planning problem of mobile ro-bots. These results cover a large range of the problems that are frequently encountered in the motion planning of mobile robots both in theoretical methods and practical applications including obstacle avoidance methods, navigation and localization techniques, environmental modelling or map building methods, and vision signal processing etc. Different methods such as potential fields, reactive behaviours, neural-fuzzy based methods, motion control methods and so on are studied. Through this book and its references, the reader will definitely be able to get a thorough overview on the current research results for this specific topic in robotics. The book is intended for the readers who are interested and active in the field of robotics and especially for those who want to study and develop their own methods in motion/path planning or control for an intelligent robotic system.
Of the 300 papers presented during IROS '94, 48 were selected because they are particularly significant and characteristic for the present state of the technology of intelligent robots and systems. This book contains the selected papers in a revised and expanded form.Robotics and intelligent systems constitute a very wide and truly interdisciplinary field. The papers have been grouped into the following categories:– Sensing and Perception – Learning and Planning– Manipulation– Telerobotics and Space Robotics– Multiple Robots– Legged Locomotion– Mobile Robot Systems– Robotics in MedicineOther additional fields covered include; control, navigation and simulation. Since many researchers in robotics are now apparently interested in some combination of learning, mobile robots and robot vision, most of the articles included relate to at least one of these fields.