Displacement Estimation Based on Optical and Inertial Sensor Fusion.

Area of Science:

• Robotics and Automation
• Sensor Technology
• Navigation Systems

Background:

• Increasing demand for accurate displacement estimation in robotics and pedestrian navigation.
• Limitations of existing single-sensor systems in dynamic environments.

Purpose of the Study:

• To develop a cost-effective system for estimating linear displacement using MEMS accelerometers and optical flow sensors.
• To enhance displacement estimation accuracy through sensor fusion and advanced algorithms.

Main Methods:

• Development of data post-processing algorithms for MEMS accelerometers and optical flow sensors.
• Implementation of a complementary filter for sensor fusion.
• Integration of a zero-velocity update detection algorithm for accelerometer data.
• Construction of a test stand for linear motion validation.

Main Results:

• Individual sensors demonstrated high accuracy in displacement estimation.
• Sensor fusion yielded superior results, particularly in mitigating optical flow sensor disturbances.
• Zero-velocity detection algorithm significantly improved accelerometer-based displacement calculations.
• Comparative analysis against encoder data validated the system's performance.

Conclusions:

• The developed system effectively estimates linear displacement using affordable sensors.
• Sensor fusion enhances robustness and accuracy, making the system suitable for various applications.
• The proposed algorithms and sensor combination offer a practical solution for displacement measurement.