Simultaneous Localization and Mapping for Mobile Robots下载

weixin_39820535 2020-06-22 08:00:38

Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods
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Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods

The research book is a continuation of the authors’ previous works, which are focused on recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The book gathers selected contributions addressing a number of real-life applications including the identification of handwritten texts, watermarking techniques, simultaneous localization and mapping for mobile robots, motion control systems for mobile robots, analysis of indoor human activity, facial image quality assessment, android device controlling, processing medical images, clinical decision-making and foot progression angle detection. Given the tremendous interest among researchers in the development and applications of computer vision paradigms in the field of business, engineering, medicine, security and aviation, the book offers a timely guide for all PhD students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies.

The goal of this document is to give a tutorial introduction to the field of SLAM(Simultaneous Localization And Mapping) for mobile robots. There are numerous papers on the subject but for someone new in the field it will require many hours of research to understand many of the intricacies involved in implementing SLAM. The hope is thus to present the subject in a clear and concise manner while keeping the prerequisites required to understand the document to a minimum. It should actually be possible to sit down and implement basic SLAM after having read this paper.

The goal of this document is to give a tutorial introduction to the field of SLAM(Simultaneous Localization And Mapping) for mobile robots. There are numerous papers on the subject but for someone new in the field it will require many hours of research to understand many of the intricacies involved in implementing SLAM. The hope is thus to present the subject in a clear and concise manner while keeping the prerequisites required to understand the document to a minimum. It should actually be possible to sit down and implement basic SLAM after having read this paper.

Pose graphs have become a popular representation for solving the simultaneous localization and mapping (SLAM) problem. A pose graph is a set of robot poses connected by nonlinear constraints obtained from observations of features common to nearby poses. Optimizing large pose graphs has been a bottle

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