Humanoid Head Camera Stabilization Using a Soft Robotic Neck and a Robust Fractional Order Controller

Area of Science:

• Robotics
• Biomechanical Engineering
• Control Systems

Background:

• Humanoid robots experience head camera disturbances during locomotion due to torso inclination.
• Current stabilization methods rely on software corrections or mechanical motion cancellation.
• Bio-inspired strategies offer potential for more natural and compliant head movements.

Purpose of the Study:

• To propose and validate a novel mechanical approach for humanoid robot head camera stabilization.
• To investigate the effectiveness of a bio-inspired soft neck for head movement.
• To compare classical PID and fractional order control for stabilizing a soft robotic neck.

Main Methods:

• Development of a bio-inspired soft neck for a humanoid robot.
• Implementation and comparison of a Proportional-Integral-Derivative (PID) controller and a fractional order controller.
• Extensive experimental validation including real robot movements, varying head loads, and transient disturbances.

Main Results:

• The fractional order controller significantly outperformed the PID controller.
• The proposed soft neck approach demonstrated enhanced robustness and performance in head camera stabilization.
• Experimental results validated the superiority of the fractional order control strategy.

Conclusions:

• A bio-inspired soft neck offers an effective mechanical solution for humanoid robot head camera stabilization.
• Fractional order control provides superior performance and robustness for complex, nonlinear soft robotic systems.
• This approach enables more natural and stable head movements in humanoid robots during locomotion.