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On the Validation of the Proper Generalized Decomposition Method with Finite Element Method: 3D Heat Problem Under Cyclic Loading Read chapter Read first chapter

2019 | OriginalPaper | Chapter

UKF-Assisted SLAM for 4WDDMR Localization and Mapping

Authors : Abdulkader Joukhadar, Dalia Kass Hanna, Andreas Müller, Christoph Stöger

Published in: Mechanism, Machine, Robotics and Mechatronics Sciences

Publisher: Springer International Publishing

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Abstract

Correct mobile robot localization requires precise knowledge of the robot’s pose in plane, i.e. the Cartesian x and y coordinates and yaw angle \( \theta \). Mobile robot pose information estimated from on-board odmetry sensors is not fully trusted and it suffers from unceratinties exerted by the robot incorporated with actuators nonlinearities and robot mechanical complexities which lead to a low degree of believe (DoB) of the robot localization. The present paper provides Unscented Kalman Filter (UKF) based approach assisted robot localization to provide trusted information with high DoB for the mobile robot’s pose. Particularly, estimating the current situation of the robot navigation system is complex due to the above mentioned phenomenons. An efficient and accurate estimation technique which applies probabilistic algorithm based UKF is proposed. The proposed technique is implemented and verified using MATLAB/SIMULINK®. Both practical and simulation results have demonstrated the vitality of the proposed estimation approach.

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Metadata
Title
UKF-Assisted SLAM for 4WDDMR Localization and Mapping
Authors
Abdulkader Joukhadar
Dalia Kass Hanna
Andreas Müller
Christoph Stöger
Copyright Year
2019
Book
Mechanism, Machine, Robotics and Mechatronics Sciences

Print ISBN: 978-3-319-89910-7

Electronic ISBN: 978-3-319-89911-4

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-319-89911-4_19

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