As mobile robots become more common in general knowledge and practices, as opposed to simply in research labs, there is an increased need for the introduction and methods to Simultaneous Localization and Mapping (SLAM) and its techniques and concepts related to robotics.
Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods investigates the complexities of the theory of probabilistic localization and mapping of mobile robots as well as providing the most current and concrete developments. This reference source aims to be useful for practitioners, graduate and postgraduate students, and active researchers alike.
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Dr. Juan-Antonio Fernández-Madrigal holds a PhD in Computer Science and is tenured Associate Professor in the University of Málaga (Spain). He has been teaching since 1998 in graduate and post-graduate courses on real-time systems, control engineering and robotics. He has supervised PhD theses on cognitive robotics and probabilistic localization and mapping for mobile robots and a relevant number of BSc and MSc theses on very diverse subjects. His research work has been developed mainly on different aspects of the modeling of the environment for mobile robots, cognitive robotics and robotic software development. He has three books published internationally and nearly 80 scientific papers on these and other topics. He has been involved in different roles in regional, national and European research projects and is co-inventor of several patents. Regarding his personal interests, they currently include programming, drawing and writing, having authored five sci-fi books in Spanish and more than a hundred short stories.
Dr. José Luis Blanco Claraco is a Lecturer in the University of Málaga (Spain), where he has taught in graduate courses on mechatronics and material science. He obtained a PhD on mobile robotics from the same university in 2009. His research interests include estimation theory, mobile robot navigation, large-scale map building and computer vision. Since 2005 he has participated in several national and European research projects, as well as research collaborations with private companies. As a result, he has published more than 40 scientific papers and is co-inventor of three patents and one utility model. He is also an active supporter of Open Source initiatives, having participated in more than 10 software projects, most remarkably in the Mobile Robot Programming Toolkit (MRPT), which he started in 2005 and still actively maintains at present. Among his non-academic interests, he collaborates in popular science blogs aimed at the Spanish speaking community.
Fernandez-Madrigal and Claraco (both U. of Malaga, Spain) examine how mobile robots designed to interact with humans in service environments know where they are, where other things are, and how to get where they are needed. Writing for practitioners and graduate students, they cover robotic, probabilistic, and statistical basics; robot motion and sensor models; mobile robot localization with recursive Bayesian filters; types and constructions of maps for mobile robots; the Bayesian approach to simultaneous localization and mapping (SLAM); and advanced SLAM techniques --Annotation ©2012 Book News Inc. Portland, OR
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