{"product_id":"state-estimation-for-robotics-second-edition-9781009299893","title":"State Estimation for Robotics: Second Edition","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThis book covers state estimation methods for robotics, including classical and modern topics such as batch estimation, Bayes filter, sigmapoint and particle filters, robust estimation, and continuous-time trajectory estimation. It also covers practical advice on sensor models and applications in robotic systems. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 530 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 01 February 2024\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Cambridge University Press\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eRobotics is a rapidly evolving field that relies heavily on the accurate estimation of a robot's state, particularly its position and orientation, using noisy sensor data. This comprehensive book is designed to cater to students and practitioners in the realm of robotics, offering a comprehensive overview of classical state estimation methods while also delving into important modern topics such as batch estimation, Bayes filters, sigmapoint and particle filters, robust estimation for outlier rejection, and continuous-time trajectory estimation. Given that most robots operate in three-dimensional environments, the book provides common sensor models, including camera and laser rangefinder, and practical guidance on how to carry out state estimation for rotational state variables.\u003cbr\u003e\u003cbr\u003eThe book encompasses a wide range of robotic applications, including point-cloud alignment, pose-graph relaxation, bundle adjustment, and simultaneous localization and mapping. In this expanded second edition, readers will find valuable additions such as a new chapter on variational inference, a dedicated section on inertial navigation, a more comprehensive introduction to probability concepts, and a primer on matrix calculus. These enhancements further enrich the book's content and make it an invaluable resource for anyone interested in advancing their knowledge and expertise in robotics.\u003cbr\u003e\u003cbr\u003eWhether you are a student pursuing a degree in robotics or a professional seeking to enhance your skills in state estimation and its applications, this book is an essential guide. It provides a solid foundation in classical estimation methods, while also introducing you to the latest advancements in the field, enabling you to tackle complex robotic tasks with confidence and efficiency.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 1239g\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781009299893\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 2 Revised edition\u003c\/p\u003e","brand":"Timothy D.Barfoot","offers":[{"title":"Hardback","offer_id":45290051109114,"sku":"9781009299893","price":66.63,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1706897210519_book.jpg?v=1707034240","url":"https:\/\/shulphink.com\/products\/state-estimation-for-robotics-second-edition-9781009299893","provider":"Shulph Ink","version":"1.0","type":"link"}