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About this product
Product Identifiers
PublisherNow Publishers
ISBN-101601987587
ISBN-139781601987587
eBay Product ID (ePID)240025144
Product Key Features
Number of Pages86 Pages
Publication NameParticle Filters for Robot Navigation
LanguageEnglish
Publication Year2014
SubjectRobotics
TypeTextbook
Subject AreaTechnology & Engineering
AuthorWolfram Burgard, Cyrill Stachniss
SeriesFoundations and Trends in Robotics Ser.
FormatTrade Paperback
Dimensions
Item Height0.2 in
Item Weight4.8 Oz
Item Length9.2 in
Item Width6.1 in
Additional Product Features
Intended AudienceScholarly & Professional
Table Of Content1: Particle Filters for Robot Navigation 2: Robot Localization with Particle Filters 3: Simultaneous Localization and Mapping using Particle Filters 4: Information-Driven Exploration 5: Conclusion. References.
SynopsisThis primer describes particle filters and relevant applications in the context of robot navigation and illustrates that these filters are powerful tools that can robustly estimate the state of the robot and its environment., Autonomous navigation is an essential capability for mobile robots. In order to operate robustly, a robot needs to know what the environment looks like, where it is in its environment, and how to navigate within it. Particle Filters for Robot Navigation summarizes approaches that address these three problems and that use particle filters as their main underlying model for representing beliefs. It illustrates that these filters are powerful tools that can robustly estimate the state of the robot and its environment and that they are also well-suited to making decisions about how to navigate in order to minimize a robot's uncertainty about its own position and the state of the environment. They offer a series of attractive capabilities, including the ability to deal with non-Gaussian distributions and nonlinear sensor and motion models. Particle filters have been used for almost twenty years in robotics and have become a standard means for a series of tasks. Particle Filters for Robot Navigation is an ideal primer for anyone interested in the research and application of these filters in robotics.
