Beyond Odometry Accuracy: How Encoder Resolution and IMU Fusion Affect Particle Filter Localization in Differential-Drive Robots

Encoder resolution and sensor fusion architecture directly influence odometric drift in autonomous mobile robots (AMRs), yet their interaction with particle filter localization remains insufficiently characterized. This study evaluates four encoder resolutions (90, 512, 1024, and 4096 PPR) in wheel-odometry-only (System A) and EKF-based IMU-fused (System B) configurations across multiple navigation scenarios using ROS AMCL localization. Increasing resolution significantly reduced drift, with 512 PPR achieving most of the improvement observed at 4096 PPR and diminishing returns beyond 1024 PPR. IMU fusion consistently improved odometry accuracy and reduced variance, although its benefit depended on trajectory complexity rather than encoder resolution alone. However, improved odometry did not uniformly translate into improved localization. In several cases, the IMU-fused system exhibited reduced AMCL stability despite lower odometric drift. These results demonstrate that encoder selection and sensor fusion must be considered alongside particle filter parameterization, highlighting the importance of estimator compatibility in ROS-based AMR localization architectures.

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Publication Details

Journal
Robotics
Published
2026-08-25
DOI
https://doi.org/10.3390/robotics15090164
Primary Topic
Robotics and Sensor-Based Localization
Type
article
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article

Beyond Odometry Accuracy: How Encoder Resolution and IMU Fusion Affect Particle Filter Localization in Differential-Drive Robots

Thu Soe Min, Bhuvaneswari Thangavel, Yong Bin Lim, Muhammad bin Hishamuddin
Robotics
Robotics and Sensor-Based Localization
article

Beyond Odometry Accuracy: How Encoder Resolution and IMU Fusion Affect Particle Filter Localization in Differential-Drive Robots

Thu Soe Min, Bhuvaneswari Thangavel, Yong Bin Lim, Muhammad bin Hishamuddin
article en

Abstract

Encoder resolution and sensor fusion architecture directly influence odometric drift in autonomous mobile robots (AMRs), yet their interaction with particle filter localization remains insufficiently characterized. This study evaluates four encoder resolutions (90, 512, 1024, and 4096 PPR) in wheel-odometry-only (System A) and EKF-based IMU-fused (System B) configurations across multiple navigation scenarios using ROS AMCL localization. Increasing resolution significantly reduced drift, with 512 PPR achieving most of the improvement observed at 4096 PPR and diminishing returns beyond 1024 PPR. IMU fusion consistently improved odometry accuracy and reduced variance, although its benefit depended on trajectory complexity rather than encoder resolution alone. However, improved odometry did not uniformly translate into improved localization. In several cases, the IMU-fused system exhibited reduced AMCL stability despite lower odometric drift. These results demonstrate that encoder selection and sensor fusion must be considered alongside particle filter parameterization, highlighting the importance of estimator compatibility in ROS-based AMR localization architectures.

RoboticsVol. 15(9)
Multimedia University (MY), Telekom Malaysia Berhad (Malaysia) (MY)
Openalex Percentile: Top 6%
Robotics and Sensor-Based Localization
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