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IMU Error Propagation in Position Reconstruction and Its Mitigation Through Task-Informed Dual-IMU Constrained
Rachele Rossanigo1, Diletta Balta1, Niccolò Tortarolo1
1Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy.
Sensors (Basel, Switzerland)
|July 15, 2026
Summary
This study introduces a new Constrained Redundant Optimization Pipeline (CROP) for golf putting analysis using inertial measurement units (IMUs). CROP significantly improves putter trajectory reconstruction accuracy by reducing errors.
Area of Science:
- Sports Science
- Biomechanics
- Sensor Technology
Background:
- Inertial measurement units (IMUs) offer a low-cost solution for analyzing golf putting.
- However, IMU-based putter trajectory reconstruction faces limitations due to sensor errors, fusion tuning, and integration drift.
Purpose of the Study:
- To analyze error propagation in standard IMU reconstruction pipelines.
- To propose and evaluate a novel Constrained Redundant Optimization Pipeline (CROP) for enhanced accuracy.
Main Methods:
- A standard IMU pipeline involving orientation estimation and double integration was analyzed.
- The proposed CROP pipeline utilized redundant IMU data and kinematic constraints for optimization.
- 23 putting strokes were recorded using two IMUs and a stereophotogrammetric system.
Main Results:
- CROP reduced median RMS error in velocity by approximately 40% (16.5 to 9.9 cm/s).
- CROP reduced median RMS error in position by approximately 63% (23.2 to 8.5 cm).
- The proposed method demonstrated reduced drift and improved trajectory reconstruction compared to standard methods.
Conclusions:
- The Constrained Redundant Optimization Pipeline (CROP) significantly enhances IMU-based golf putting analysis.
- The findings suggest CROP offers improved accuracy and reduced drift for trajectory reconstruction.
- Further advancements are needed for precise real-world field applications.
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