Study of variation in human upper body parameters and motion for use in robotics based simulation

Area of Science:

• Biomechanics
• Human Motion Analysis
• Robotics

Background:

• Evaluating the human-likeness of simulated motion is critical for robotics and animation.
• Understanding natural human motion variability is essential for creating realistic simulations.
• Previous studies have focused on kinematic and dynamic parameters of human movement.

Purpose of the Study:

• To quantify variations in human upper body motion during activities of daily living (ADLs).
• To establish a reference for evaluating the quality of simulated human motion.
• To determine the contribution of subject-specific parameters and joint angles to hand position variance.

Main Methods:

• Collected motion capture data from eight adults performing three ADLs (hair brushing, drinking, door opening).
• Utilized an eight-camera Vicon motion analysis system for data acquisition.
• Analyzed variance in subject parameters (link lengths), joint angles (Euler rotations), and hand positions using forward kinematics.

Main Results:

• Variances in joint angles were comparable in magnitude to the root mean squared error of motion simulations.
• Reducing subject parameter and joint angle variance resulted in a proportionally small decrease in hand position variance.
• Using average subject parameters had a minor effect on hand position variance, while modifying joint angles had a greater but still limited impact.

Conclusions:

• Subject-specific parameters and joint angle variations have a limited influence on the overall hand position variance in human upper body motion.
• These findings provide a basis for developing quantitative methods to assess the human likeness of artificial movements.
• The study highlights the need for refined approaches to accurately simulate and evaluate human motion in various applications.