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As for uncertainties of ranging and direction angle in the ultrasonic sensor measurement, an ultrasonic distance measurement model is first of all proposed for representing these uncertainties through analyzing working principle of the ultrasonic sensor, which can be adopted to detect the contour of wall plan and cylinder. Moreover, the Dezert-Smarandache Theory (DSmT) method is employed to fuse the uncertainty data measured by using the ultrasonic sensor. Next, Extended Hough Transform (EHT) and Least Square Method (LSM) are combined to identify the environmental contour. Then the measurement uncertainty of the ultrasonic sensor is analyzed for setting the threshold Th used for distinguishing line and cylinder, and detection range of the cylinder radius is estimated. Finally, we build an indoor environment and design the ultrasonic sensor hardware system to detect the indoor environment for experimental verification. The indoor environment contour obtained in the experimental results is consistent with the real environment, which illustrate the feasibility and effectiveness of the proposed method. The proposed method has certain reference value for research of simultaneous localization and mapping (SLAM) of the mobile robot.
This book constitutes the refereed proceedings of the 5th International Symposium on Advances in Signal Processing and Intelligent Recognition Systems, SIRS 2019, held in Trivandrum, India, in December 2019. The 19 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 63 submissions. The papers cover wide research fields including information retrieval, human-computer interaction (HCI), information extraction, speech recognition.
Visual Perception and Control of Underwater Robots covers theories and applications from aquatic visual perception and underwater robotics. Within the framework of visual perception for underwater operations, image restoration, binocular measurement, and object detection are addressed. More specifically, the book includes adversarial critic learning for visual restoration, NSGA-II-based calibration for binocular measurement, prior knowledge refinement for object detection, analysis of temporal detection performance, as well as the effect of the aquatic data domain on object detection. With the aid of visual perception technologies, two up-to-date underwater robot systems are demonstrated. The first system focuses on underwater robotic operation for the task of object collection in the sea. The second is an untethered biomimetic robotic fish with a camera stabilizer, its control methods based on visual tracking. The authors provide a self-contained and comprehensive guide to understand underwater visual perception and control. Bridging the gap between theory and practice in underwater vision, the book features implementable algorithms, numerical examples, and tests, where codes are publicly available. Additionally, the mainstream technologies covered in the book include deep learning, adversarial learning, evolutionary computation, robust control, and underwater bionics. Researchers, senior undergraduate and graduate students, and engineers dealing with underwater visual perception and control will benefit from this work.
The material of this book encompasses many disciplines, including visible, infrared, far infrared, millimeter wave, microwave, radar, synthetic aperture radar, and electro-optical sensors as well as the very dynamic topics of image processing, computer vision and pattern recognition. This book is composed of six parts: * Advanced background modeling for surveillance * Advances in Tracking in Infrared imagery * Methods for Pose estimation in Ultrasound and LWIR imagery * Recognition in multi-spectral and synthetic aperture radar * Fusion of disparate sensors * Smart Sensors
The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut
A theoretical analysis of the effects of drilling on subsequent temperature measurements in a well, with application to data obtained in permafrost near Barrow, Alaska.
For many years technical and medical diagnostics has been the area of intensive scientific research. It covers well-established topics as well as emerging developments in control engineering, artificial intelligence, applied mathematics, pattern recognition and statistics. At the same time, a growing number of applications of different fault diagnosis methods, especially in electrical, mechanical, chemical and medical engineering, is being observed. This monograph contains a collection of 44 carefully selected papers contributed by experts in technical and medical diagnostics, and constitutes a comprehensive study of the field. The aim of the book is to show the bridge between technical and medical diagnostics based on artificial intelligence methods and techniques. It is divided into four parts: I. Soft Computing in Technical Diagnostics, II. Medical Diagnostics and Biometrics, III. Robotics and Computer Vision, IV. Various Problems of Technical Diagnostics. The monograph will be of interest to scientists as well as academics dealing with the problems of designing technical and medical diagnosis systems. Its target readers are also junior researchers and students of computer science, artificial intelligence, control or robotics.