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Automated gripping and handling tasks offer a great rationalization potential but they are still dificult to realize. This book shows you how to ensure process reliability on the basis of combining the right components with advanced application know-how. By explaining basic preconditions of the gripping process and highlighting the milestones of automation history, we guide you all the way through to the center of the handling process - the workpiece. Its ambient conditions and setup are clearly defined as well as the process of setting grippers in motion. Starting with simple linear movements up to multiaxis kinematics, you are provided with the details for practical solutions. A whole range of current applications illustrates the variety and opportunities of automation in daily business--

Robots, Industrial. --- Materials handling --- Robot hands. --- Automation. --- Hands, Robot --- Robots --- Handling of materials --- Material handling --- Materials --- Mechanical handling --- Plant engineering --- Plant layout --- Production engineering --- Shipment of goods --- Industrial robots --- Automatic machinery --- Handling and transportation

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This book focuses on light invariant bare hand gesture recognition while there is no restriction on the types of gestures. Observations and results have confirmed that this research work can be used to remotely control a robotic hand using hand gestures. The system developed here is also able to recognize hand gestures in different lighting conditions. The pre-processing is performed by developing an image-cropping algorithm that ensures only the area of interest is included in the segmented image. The segmented image is compared with a predefined gesture set which must be installed in the recognition system. These images are stored and feature vectors are extracted from them. These feature vectors are subsequently presented using an orientation histogram, which provides a view of the edges in the form of frequency. Thereby, if the same gesture is shown twice in different lighting intensities, both repetitions will map to the same gesture in the stored data. The mapping of the segmented image's orientation histogram is firstly done using the Euclidian distance method. Secondly, the supervised neural network is trained for the same, producing better recognition results. An approach to controlling electro-mechanical robotic hands using dynamic hand gestures is also presented using a robot simulator. Such robotic hands have applications in commercial, military or emergency operations where human life cannot be risked. For such applications, an artificial robotic hand is required to perform real-time operations. This robotic hand should be able to move its fingers in the same manner as a human hand. For this purpose, hand geometry parameters are obtained using a webcam and also using KINECT. The parameter detection is direction invariant in both methods. Once the hand parameters are obtained, the fingers’ angle information is obtained by performing a geometrical analysis. An artificial neural network is also implemented to calculate the angles. These two methods can be used with only one hand, either right or left. A separate method that is applicable to both hands simultaneously is also developed and fingers angles are calculated. The contents of this book will be useful for researchers and professional engineers working on robotic arm/hand systems.

Robust control. --- Robot hands --- Control. --- Hands, Robot --- Robustness (Control systems) --- Engineering. --- Artificial intelligence. --- Control engineering. --- Robotics. --- Automation. --- Robotics and Automation. --- Artificial Intelligence (incl. Robotics). --- Robots --- Automatic control --- Artificial Intelligence. --- Control and Systems Theory. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Automatic factories --- Automatic production --- Computer control --- Engineering cybernetics --- Factories --- Industrial engineering --- Mechanization --- Assembly-line methods --- Automatic machinery --- CAD/CAM systems --- Robotics --- Automation --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Programmable controllers

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Hand --- Diagnostic imaging. --- Arm --- Arms (Anatomy) --- Extremities, Upper --- Extremity, Upper --- Limb, Pectoral --- Limb, Thoracic --- Limb, Upper --- Pectoral limb --- Pectoral limbs --- Thoracic limb --- Thoracic limbs --- Upper extremities --- Upper extremity --- Upper limb --- Upper limbs --- Extremities (Anatomy) --- Clinical imaging --- Imaging, Diagnostic --- Medical diagnostic imaging --- Medical imaging --- Noninvasive medical imaging --- Diagnosis, Noninvasive --- Imaging systems in medicine --- Hands --- Paw --- Paws --- Left- and right-handedness --- Imaging.

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This book introduces the challenges of robotic tactile perception and task understanding, and describes an advanced approach based on machine learning and sparse coding techniques. Further, a set of structured sparse coding models is developed to address the issues of dynamic tactile sensing. The book then proves that the proposed framework is effective in solving the problems of multi-finger tactile object recognition, multi-label tactile adjective recognition and multi-category material analysis, which are all challenging practical problems in the fields of robotics and automation. The proposed sparse coding model can be used to tackle the challenging visual-tactile fusion recognition problem, and the book develops a series of efficient optimization algorithms to implement the model. It is suitable as a reference book for graduate students with a basic knowledge of machine learning as well as professional researchers interested in robotic tactile perception and understanding, and machine learning.

Robot hands. --- Robots --- Programming. --- Computer science. --- Artificial intelligence. --- Image processing. --- Pattern recognition. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Pattern Recognition. --- Image Processing and Computer Vision. --- Robot programming --- Computer programming --- Hands, Robot --- Optical pattern recognition. --- Computer vision. --- Artificial Intelligence. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Optical data processing. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Optical equipment

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This book is an essential guide for rheumatologists using ultrasound to study musculoskeletal structures and diagnose rheumatic diseases of the hand. A fundamental understanding of anatomy is key to identifying and interpreting pathological findings on imaging. This book provides comprehensive knowledge about both gross anatomy and, more importantly, comparative imaging anatomy, as depicted by ultrasound, X-ray, and MRI of the hand. This foundation enables clinicians to readily identify pathologic findings and thus improve diagnostic skills. The authors also offer step-by-step guidelines for using ultrasound, with comprehensive descriptions about body and transducer position, sonographic terminology, and anatomical landmarks in different planes of the hand. This book is an indispensable reference for rheumatologists and rheumatology residents using musculoskeletal ultrasound in clinical practice.

Medicine. --- Radiology. --- Rheumatology. --- Medicine & Public Health. --- Ultrasound. --- Diagnostic Radiology. --- Musculoskeletal system --- Rheumatism --- Hand --- Ultrasonic imaging. --- Diseases --- Diagnosis. --- Hands --- Paw --- Paws --- Arm --- Left- and right-handedness --- Rheumatic diseases --- Collagen diseases --- Locomotor system --- Musculo-skeletal system --- Skeletomuscular system --- Diagnosis, Ultrasonic. --- Radiology, Medical. --- Clinical radiology --- Radiology, Medical --- Radiology (Medicine) --- Medical physics --- Diagnosis, Ultrasonic --- Diagnostic sonography --- Diagnostic ultrasonics --- Diagnostic ultrasonography --- Diagnostic ultrasound --- Medical diagnostic ultrasonic imaging --- Medical ultrasonography --- Ultrasonic diagnosis --- Ultrasonic diagnostic imaging --- Ultrasonic imaging --- Ultrasonic waves --- Diagnostic imaging --- Ultrasonics in medicine --- Internal medicine --- Connective tissues --- Joints --- Diagnostic use --- Radiological physics --- Physics --- Radiation