Enhancing Indoor Mobile Robot Localization through the Integration of Multi-Sensor Fusion Algorithms

This paper presents an innovative approach that combines visual odometry, Inertial Measurement Unit (IMU), and wheel odometry, using the Extended Kalman Filter and Unscented Kalman Filter to enhance mobile robot localization and mapping. The primary goal is to improve localization accuracy and robus...

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Bibliographic Details

Published in:	2024 1st International Conference on Robotics, Engineering, Science, and Technology (RESTCON) pp. 101 - 105
Main Authors:	Yatigul, Rut, Pudchuen, Noppadol, Blattler, Aran, Jitviriya, Wisanu
Format:	Conference Proceeding
Language:	English
Published:	IEEE 16.02.2024
Subjects:	Extended Kalman Filter Filtering algorithms Inertial Measurement Unit (IMU) Kalman filters Location awareness Measurement units Multi-sensor fusion Robustness Simultaneous localization and mapping Unscented Kalman Filter Visual odometry Wheels
Online Access:	Get full text
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