{"product_id":"multimodal-perception-and-secure-state-estimation-for-robotic-mobility-platforms-hardcover","title":"Multimodal Perception and Secure State Estimation for Robotic Mobility Platforms - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eXinghua Liu\u003c\/b\u003e (Author), \u003cb\u003eRui Jiang\u003c\/b\u003e (Author), \u003cb\u003eBadong Chen\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003cb\u003eMultimodal Perception and Secure State Estimation for Robotic Mobility Platforms\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003cb\u003eEnables readers to understand important new trends in multimodal perception for mobile robotics \u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eThis book provides a novel perspective on secure state estimation and multimodal perception for robotic mobility platforms such as autonomous vehicles. It thoroughly evaluates filter-based secure dynamic pose estimation approaches for autonomous vehicles over multiple attack signals and shows that they outperform conventional Kalman filtered results. \u003c\/p\u003e\u003cp\u003eAs a modern learning resource, it contains extensive simulative and experimental results that have been successfully implemented on various models and real platforms. To aid in reader comprehension, detailed and illustrative examples on algorithm implementation and performance evaluation are also presented. Written by four qualified authors in the field, sample topics covered in the book include: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eSecure state estimation that focuses on system robustness under cyber-attacks\u003c\/li\u003e \u003cli\u003eMulti-sensor fusion that helps improve system performance based on the complementary characteristics of different sensors\u003c\/li\u003e \u003cli\u003eA geometric pose estimation framework to incorporate measurements and constraints into a unified fusion scheme, which has been validated using public and self-collected data\u003c\/li\u003e \u003cli\u003eHow to achieve real-time road-constrained and heading-assisted pose estimation\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eThis book will appeal to graduate-level students and professionals in the fields of ground vehicle pose estimation and perception who are looking for modern and updated insight into key concepts related to the field of robotic mobility platforms.\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eEnables readers to understand important new trends in multimodal perception for mobile robotics \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThis book provides a novel perspective on secure state estimation and multimodal perception for robotic mobility platforms such as autonomous vehicles. It thoroughly evaluates filter-based secure dynamic pose estimation approaches for autonomous vehicles over multiple attack signals and shows that they outperform conventional Kalman filtered results. \u003c\/p\u003e\u003cp\u003eAs a modern learning resource, it contains extensive simulative and experimental results that have been successfully implemented on various models and real platforms. To aid in reader comprehension, detailed and illustrative examples on algorithm implementation and performance evaluation are also presented. Written by four qualified authors in the field, sample topics covered in the book include: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eSecure state estimation that focuses on system robustness under cyber-attacks\u003c\/li\u003e \u003cli\u003eMulti-sensor fusion that helps improve system performance based on the complementary characteristics of different sensors\u003c\/li\u003e \u003cli\u003eA geometric pose estimation framework to incorporate measurements and constraints into a unified fusion scheme, which has been validated using public and self-collected data\u003c\/li\u003e \u003cli\u003eHow to achieve real-time road-constrained and heading-assisted pose estimation\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eThis book will appeal to graduate-level students and professionals in the fields of ground vehicle pose estimation and perception who are looking for modern and updated insight into key concepts related to the field of robotic mobility platforms.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eXinghua Liu\u003c\/b\u003e is a Professor with Xi'an University of Technology. His research interests are secure state estimation and control, cyber-physical systems, and artificial Intelligence. \u003c\/p\u003e \u003cp\u003e\u003cb\u003eRui Jiang\u003c\/b\u003e is a Staff Algorithm Engineer at the OmniVision Technologies Inc., and an Adjunct Lecturer with the National University of Singapore. His research interests are intelligent sensing, and perception for robotic systems. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eBadong Chen\u003c\/b\u003e is a Professor with Xi'an Jiaotong University. His research interests are signal processing, machine learning, artificial intelligence, neural engineering, and robotics. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eShuzhi Sam Ge\u003c\/b\u003e is a Professor with the National University of Singapore and an honorary Director of Institute for Future, Qingdao University, China. His research interests are adaptive control, robotics, and artificial Intelligence.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 224\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.56 x 9 x 6 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e September 21, 2022\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47213347995897,"sku":"9781119876014","price":158.4,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/cW8rQ3pxdTVqR3I5Q25TdkhKTXJWQT09.webp?v=1768104626","url":"https:\/\/bookscloud.io\/products\/multimodal-perception-and-secure-state-estimation-for-robotic-mobility-platforms-hardcover","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}