CPG-based generation strategy of variable rhythmic chewing movements for a dental testing chewing robot

Area of Science:

• Biomechanics
• Robotics
• Dental Materials Science

Background:

• Chewing movement patterns adapt to varied environments, impacting dental prosthesis wear.
• Accurate simulation of these dynamic movements is crucial for testing dental materials.

Purpose of the Study:

• To generate variable rhythmic chewing movements for dental testing equipment.
• To develop a Central Pattern Generator (CPG) model for simulating diverse chewing patterns.

Main Methods:

• Utilized a six-axis parallel chewing robot (DUT-2).
• Extracted four movement variances: period, offset, amplitude, and mode.
• Proposed a CPG model based on morphed phase oscillators with a specific modulation method.
• Simulated incisor trajectories and analyzed bite force on virtual and physical prototypes.

Main Results:

• Achieved low relative errors for offset (4.14%) and amplitude (0.74%) in the z-direction.
• Demonstrated smooth transitions during gradually increasing and bilateral movements.
• Obtained average relative errors and bias of 4.15% and 1.08% for maximum bite force in two-body contact.
• Noted decreased accuracy with food involvement (13.18% and 2.50%).

Conclusions:

• The CPG model provides a bionic and explicit method for generating variable chewing movements.
• The model can replicate chewing variations related to preferences and food properties.
• High repeatability of bite force supports repetitive wear testing and studying variance effects on prosthesis wear performance.