Multi-Sensor Fusion Framework for Reliable Localization and Trajectory Tracking of Mobile Robot by Integrating UWB, Odometry, and AHRS
This paper presents a multi-sensor fusion framework for the accurate indoor localization and trajectory tracking of a differential-drive mobile robot. The proposed system integrates Ultra-Wideband (UWB) trilateration, wheel odometry, and Attitude and Heading Reference System (AHRS) data using a Kalm...
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MDPI AG
2025-07-01
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| Series: | Biomimetics |
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| Online Access: | https://www.mdpi.com/2313-7673/10/7/478 |
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| author | Quoc-Khai Tran Young-Jae Ryoo |
| author_facet | Quoc-Khai Tran Young-Jae Ryoo |
| author_sort | Quoc-Khai Tran |
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| description | This paper presents a multi-sensor fusion framework for the accurate indoor localization and trajectory tracking of a differential-drive mobile robot. The proposed system integrates Ultra-Wideband (UWB) trilateration, wheel odometry, and Attitude and Heading Reference System (AHRS) data using a Kalman filter. This fusion approach reduces the impact of noisy and inaccurate UWB measurements while correcting odometry drift. The system combines raw UWB distance measurements with wheel encoder readings and heading information from an AHRS to improve robustness and positioning accuracy. Experimental validation was conducted through repeated closed-loop trajectory trials. The results demonstrate that the proposed method significantly outperforms UWB-only localization, yielding reduced noise, enhanced consistency, and lower Dynamic Time Warping (DTW) distances across repetitions. The findings confirm the system’s effectiveness and suitability for real-time mobile robot navigation in indoor environments. |
| format | Article |
| id | doaj-art-0ef8d98a769d45aca5c9259d5985e4d0 |
| institution | Kabale University |
| issn | 2313-7673 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomimetics |
| spelling | doaj-art-0ef8d98a769d45aca5c9259d5985e4d02025-08-20T03:58:26ZengMDPI AGBiomimetics2313-76732025-07-0110747810.3390/biomimetics10070478Multi-Sensor Fusion Framework for Reliable Localization and Trajectory Tracking of Mobile Robot by Integrating UWB, Odometry, and AHRSQuoc-Khai Tran0Young-Jae Ryoo1Faculty of Electrical and Electronics Engineering, Vietnam Aviation Academy, Ho Chi Minh City 70000, VietnamDepartment of Electrical Engineering, Mokpo National University, Jeonnam 58554, Republic of KoreaThis paper presents a multi-sensor fusion framework for the accurate indoor localization and trajectory tracking of a differential-drive mobile robot. The proposed system integrates Ultra-Wideband (UWB) trilateration, wheel odometry, and Attitude and Heading Reference System (AHRS) data using a Kalman filter. This fusion approach reduces the impact of noisy and inaccurate UWB measurements while correcting odometry drift. The system combines raw UWB distance measurements with wheel encoder readings and heading information from an AHRS to improve robustness and positioning accuracy. Experimental validation was conducted through repeated closed-loop trajectory trials. The results demonstrate that the proposed method significantly outperforms UWB-only localization, yielding reduced noise, enhanced consistency, and lower Dynamic Time Warping (DTW) distances across repetitions. The findings confirm the system’s effectiveness and suitability for real-time mobile robot navigation in indoor environments.https://www.mdpi.com/2313-7673/10/7/478indoor localizationsensor fusionUltra-Wideband (UWB)wheel odometryAttitude and Heading Reference System (AHRS)Kalman Filter |
| spellingShingle | Quoc-Khai Tran Young-Jae Ryoo Multi-Sensor Fusion Framework for Reliable Localization and Trajectory Tracking of Mobile Robot by Integrating UWB, Odometry, and AHRS Biomimetics indoor localization sensor fusion Ultra-Wideband (UWB) wheel odometry Attitude and Heading Reference System (AHRS) Kalman Filter |
| title | Multi-Sensor Fusion Framework for Reliable Localization and Trajectory Tracking of Mobile Robot by Integrating UWB, Odometry, and AHRS |
| title_full | Multi-Sensor Fusion Framework for Reliable Localization and Trajectory Tracking of Mobile Robot by Integrating UWB, Odometry, and AHRS |
| title_fullStr | Multi-Sensor Fusion Framework for Reliable Localization and Trajectory Tracking of Mobile Robot by Integrating UWB, Odometry, and AHRS |
| title_full_unstemmed | Multi-Sensor Fusion Framework for Reliable Localization and Trajectory Tracking of Mobile Robot by Integrating UWB, Odometry, and AHRS |
| title_short | Multi-Sensor Fusion Framework for Reliable Localization and Trajectory Tracking of Mobile Robot by Integrating UWB, Odometry, and AHRS |
| title_sort | multi sensor fusion framework for reliable localization and trajectory tracking of mobile robot by integrating uwb odometry and ahrs |
| topic | indoor localization sensor fusion Ultra-Wideband (UWB) wheel odometry Attitude and Heading Reference System (AHRS) Kalman Filter |
| url | https://www.mdpi.com/2313-7673/10/7/478 |
| work_keys_str_mv | AT quockhaitran multisensorfusionframeworkforreliablelocalizationandtrajectorytrackingofmobilerobotbyintegratinguwbodometryandahrs AT youngjaeryoo multisensorfusionframeworkforreliablelocalizationandtrajectorytrackingofmobilerobotbyintegratinguwbodometryandahrs |