Mobile Robot Localization via Indoor Positioning System and Odometry Fusion

Muhammad Hafil Nugraha Research Centre for Smart Mechatronics National Research and Innovation Agency Bandung, Indonesia muha167@brin.go.id Estiko Rijanto Research Centre for Smart Mechatronics National Research and Innovation Agency Bandung, Indonesia estiko.rijanto@brin.go.id Oka Mahendra Research Centre for Smart Mechatronics National Research and Innovation Agency Bandung, Indonesia oka.mahendra@brin.go.id Abstract -- Accurate localization is crucial for effectively operating mobile robots in indoor environments. This paper presents a comprehensive approach to mobile robot localization by integrating an ultrasound - based indoor positioning system (IPS) with wheel odometry data via sensor fusion techniques. The Extended Kalman Filter (EKF) fusion method combines the data from the IPS sensors and the robot's wheel odometry, providing a robust and relia ble localization solution. Extensive experiments in a controlled indoor environment reveal that the fusion - based localization system significantly enhances accuracy and precision compared to standalone systems.