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Predictive Autonomous Robot Navigation

POMDPs for robot navigation with integrated human motion prediction

Language EnglishEnglish
Book Paperback
Book Predictive Autonomous Robot Navigation Amalia Foka
Libristo code: 15200174
Publishers LAP Lambert Academic Publishing, November 2015
A primary goal in robotics research is to provide means for mobile platforms to perform autonomously... Full description
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A primary goal in robotics research is to provide means for mobile platforms to perform autonomously within their environment. Depending on the task at hand, autonomous performance can be defined as the execution by the robot, without human intervention, of certain navigational tasks. Commonly addressed navigation tasks include the localization, mapping, path planning and obstacle avoidance tasks. A probabilistic framework for the navigation tasks of localization, path planning and obstacle avoidance in dynamic environments is presented based on the Partially Observable Markov Decision Process (POMDP) model. POMDPs have the major shortcoming of their extreme computational complexity and hence they have been mainly used in robotics as high level path planners only. An hierarchical representation of POMDPs is introduced specifically designed for the autonomous robot navigation problem and termed as the Robot Navigation-Hierarchical POMDP (RNHPOMDP). Integration of human motion prediction into the navigation model is utilized with two kinds of prediction: short-term and long-term prediction. The book should be useful to students in Robotics utilizing POMDPs.

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About the book

Full name Predictive Autonomous Robot Navigation
Author Amalia Foka
Language English
Binding Book - Paperback
Date of issue 2016
Number of pages 136
EAN 9783659880070
Libristo code 15200174
Weight 221
Dimensions 150 x 220 x 8
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