A Complementary Filter Design on SE(3) to IdentifyMicro-Motions during 3D Motion Tracking.

Area of Science:

• Robotics
• Biomechanics
• Sensor Fusion

Background:

• Marker-based motion capture excels at low-frequency position estimation.
• Inertial Measurement Units (IMUs) are suitable for high-frequency orientation estimation.
• Limitations exist in capturing high-frequency or micro-motions with traditional systems.

Purpose of the Study:

• To introduce a complementary filter for enhancing 3D motion capture data.
• To integrate high-frequency acceleration signals from IMUs.
• To improve the accuracy and micro-motion detection capabilities of motion tracking.

Main Methods:

• Development of a complementary filter algorithm.
• Fusion of 3D motion capture data with IMU acceleration signals.
• Experimental evaluation of the filter's performance.

Main Results:

• The complementary filter successfully integrates IMU acceleration data.
• Improved accuracy in 3D motion tracking was demonstrated.
• Enhanced detection of micro-motions, especially in high-frequency scenarios.

Conclusions:

• The proposed filter overcomes limitations of traditional 3D motion capture systems.
• Combining IMU data significantly enhances motion tracking accuracy and detail.
• The method is beneficial for high-frequency human motion analysis and robotic applications.