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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Vydané v:	2024 1st International Conference on Robotics, Engineering, Science, and Technology (RESTCON) s. 101 - 105
Hlavní autori:	Yatigul, Rut, Pudchuen, Noppadol, Blattler, Aran, Jitviriya, Wisanu
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 16.02.2024
Predmet:	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
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