Robotic Systems: Concepts, Methodologies, Tools, and Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Robotic Systems: Concepts, Methodologies, Tools, and Applications write by Management Association, Information Resources. This book was released on 2020-01-03. Robotic Systems: Concepts, Methodologies, Tools, and Applications available in PDF, EPUB and Kindle. Through expanded intelligence, the use of robotics has fundamentally transformed a variety of fields, including manufacturing, aerospace, medicine, social services, and agriculture. Continued research on robotic design is critical to solving various dynamic obstacles individuals, enterprises, and humanity at large face on a daily basis. Robotic Systems: Concepts, Methodologies, Tools, and Applications is a vital reference source that delves into the current issues, methodologies, and trends relating to advanced robotic technology in the modern world. Highlighting a range of topics such as mechatronics, cybernetics, and human-computer interaction, this multi-volume book is ideally designed for robotics engineers, mechanical engineers, robotics technicians, operators, software engineers, designers, programmers, industry professionals, researchers, students, academicians, and computer practitioners seeking current research on developing innovative ideas for intelligent and autonomous robotics systems.
Vision Based Localization of Mobile Robots
Vision Based Localization of Mobile Robots - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Vision Based Localization of Mobile Robots write by Jason Mooberry. This book was released on 2007. Vision Based Localization of Mobile Robots available in PDF, EPUB and Kindle. "Mobile robotics is an active and exciting sub-field of Computer Science. Its importance is easily witnessed in a variety of undertakings from DARPA's Grand Challenge to NASA's Mars exploration program. The field is relatively young, and still many challenges face roboticists across the boards. One important area of research is localization, which concerns itself with granting a robot the ability to discover and continually update an internal representation of its position. Vision based sensor systems have been investigated, but to much lesser extent than other popular techniques. A custom mobile platform has been constructed on top of which a monocular vision based localization system has been implemented. The rigorous gathering of empirical data across a large group of parameters germane to the problem has led to various findings about monocular vision based localization and the fitness of the custom robot platform. The localization component is based on a probabilistic technique called Monte-Carlo Localization (MCL) that tolerates a variety of different sensors and effectors, and has further proven to be adept at localization in diverse circumstances. Both a motion model and sensor model that drive the particle filter at the algorithm's core have been carefully derived. The sensor model employs a simple correlation process that leverages color histograms and edge detection to filter robot pose estimations via the on board vision. This algorithm relies on image matching to tune position estimates based on a priori knowledge of its environment in the form of a feature library. It is believed that leveraging different computationally inexpensive features can lead to efficient and robust localization with MCL. The central goal of this thesis is to implement and arrive at such a conclusion through the gathering of empirical data. Section 1 presents a brief introduction to mobile robot localization and robot architectures, while section 2 covers MCL itself in more depth. Section 3 elaborates on the localization strategy, modeling and implementation that forms the basis of the trials that are presented toward the end of that section. Section 4 presents a revised implementation that attempts to address shortcomings identified during localization trials. Finally in section 5, conclusions are drawn about the effectiveness of the localization implementation and a path to improved localization with monocular vision is posited"--Abstract.
Vision Based Mobile Robotics: mobile robot localization using vision sensors and active probabilistic approaches
Vision Based Mobile Robotics: mobile robot localization using vision sensors and active probabilistic approaches - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Vision Based Mobile Robotics: mobile robot localization using vision sensors and active probabilistic approaches write by Emanuele Frontoni. This book was released on 2012-01-22. Vision Based Mobile Robotics: mobile robot localization using vision sensors and active probabilistic approaches available in PDF, EPUB and Kindle. The use of vision in mobile robotics in one of the main goal of this thesis. In particular novel appearance based approaches for image matching metric are introduced. These approaches are applied to the problem of mobile robot localization.Similarity measures between robot's views are used in probabilistic methods for robot pose estimation. In this field of probabilistic localization active approach are proposed allowing the robot to faster and better localize. All methods have been extensively tested using a real robot in an indoor environment.Note: the book is the publication of the PhD thesis discussed in Università Politecnica delle Marche, Ancona, Italy in 2006 by Emanuele Frontoni
Vision Based Autonomous Robot Navigation
Vision Based Autonomous Robot Navigation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Vision Based Autonomous Robot Navigation write by Amitava Chatterjee. This book was released on 2012-10-13. Vision Based Autonomous Robot Navigation available in PDF, EPUB and Kindle. This monograph is devoted to the theory and development of autonomous navigation of mobile robots using computer vision based sensing mechanism. The conventional robot navigation systems, utilizing traditional sensors like ultrasonic, IR, GPS, laser sensors etc., suffer several drawbacks related to either the physical limitations of the sensor or incur high cost. Vision sensing has emerged as a popular alternative where cameras can be used to reduce the overall cost, maintaining high degree of intelligence, flexibility and robustness. This book includes a detailed description of several new approaches for real life vision based autonomous navigation algorithms and SLAM. It presents the concept of how subgoal based goal-driven navigation can be carried out using vision sensing. The development concept of vision based robots for path/line tracking using fuzzy logic is presented, as well as how a low-cost robot can be indigenously developed in the laboratory with microcontroller based sensor systems. The book describes successful implementation of integration of low-cost, external peripherals, with off-the-shelf procured robots. An important highlight of the book is that it presents a detailed, step-by-step sample demonstration of how vision-based navigation modules can be actually implemented in real life, under 32-bit Windows environment. The book also discusses the concept of implementing vision based SLAM employing a two camera based system.
Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment
Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment write by Xiaochun Wang. This book was released on 2019-08-12. Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment available in PDF, EPUB and Kindle. This book advances research on mobile robot localization in unknown environments by focusing on machine-learning-based natural scene recognition. The respective chapters highlight the latest developments in vision-based machine perception and machine learning research for localization applications, and cover such topics as: image-segmentation-based visual perceptual grouping for the efficient identification of objects composing unknown environments; classification-based rapid object recognition for the semantic analysis of natural scenes in unknown environments; the present understanding of the Prefrontal Cortex working memory mechanism and its biological processes for human-like localization; and the application of this present understanding to improve mobile robot localization. The book also features a perspective on bridging the gap between feature representations and decision-making using reinforcement learning, laying the groundwork for future advances in mobile robot navigation research.
