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Laser-Tracker-Based Robot Pose Measurement Using PSD Spot Sensing and Multi-Sensor Fusion with Simulation Validation.

Suli Wang¹, Jing Yang¹, Xiaodan Sang¹

¹College of Physics and Telecommunication Engineering, Zhoukou Normal University, No. 6, Middle Section of Wenchang Avenue, Chuanhui District, Zhoukou 466001, China.

|March 28, 2026

Summary

This study presents a laser tracker framework for robot pose measurement, enhancing accuracy and robustness through Position Sensitive Detector (PSD) sensing, multi-sensor fusion, and simulation. The system improves precision manufacturing and robotic calibration.

Keywords:

interferometry laser tracker position sensitive detector robot pose measurement sensor fusion tracking control

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Area of Science:

Robotics
Metrology
Optical Engineering

Background:

Traditional robotic kinematic models struggle with environmental disturbances and structural uncertainties in precision manufacturing.
Laser tracker systems offer high-precision, large-volume measurement but face challenges in optical tracking stability and sensor noise.

Purpose of the Study:

To introduce a robust laser tracker-based framework for accurate robot pose measurement.
To enhance the efficacy of external references for robot pose estimation in industrial settings.

Main Methods:

Development of a Position Sensitive Detector (PSD)-based optical spot sensing subsystem with analog signal conditioning, high-speed A/D sampling, and FPGA-based centroid computation.
Integration of PSD measurements with inertial and encoder data using an extended Kalman filter within a comprehensive simulation framework.
Analysis of ranging-related effects and error-compensation mechanisms based on the interferometric ranging principle.

Main Results:

Bench experiments validated the PSD sensing chain's linearity (within ±0.9 mm displacement) and robustness under varying illumination.
An interference optical filter significantly improved measurement repeatability under background light.
Simulations demonstrated the impact of process noise tuning, time synchronization, and error sources on pose estimation accuracy.

Conclusions:

The proposed PSD-based optical tracking framework, combined with multi-sensor fusion and layered error compensation, effectively improves the robustness and positional accuracy of robot pose measurement.
The framework provides valuable guidance for developing and validating laser tracker-oriented robot pose measurement systems in complex industrial environments.