Effective locomotion at multiple stride frequencies using proprioceptive feedback on a legged microrobot

Area of Science:

• Robotics
• Bio-inspired Engineering
• Control Systems

Background:

• Small legged robots traditionally rely on fixed leg trajectories due to actuation and sensing limits.
• Advances in manufacturing now allow for multi-degree-of-freedom leg trajectories and multiple stride frequencies.
• Proprioceptive sensing and control are crucial for enhancing robot adaptability in diverse conditions.

Purpose of the Study:

• To develop an efficient estimation and control framework for leg trajectories in quadrupedal microrobots.
• To leverage concomitant sensing with piezoelectric actuation for precise robot movement.
• To explore bio-inspired leg trajectories for improved locomotion performance.

Main Methods:

• Utilized a computationally efficient framework for real-time estimation and control of leg trajectories.
• Implemented concomitant sensing with piezoelectric actuation on a quadrupedal microrobot.
• Designed and tested two bio-inspired parametric leg trajectories.

Main Results:

• Achieved accurate position estimation (<16 µm RMSE) and control (<16 µm tracking error) across stride frequencies from 10 Hz to 50 Hz.
• Demonstrated high-performance locomotion (10 Hz-30 Hz) overcoming limitations of open-loop control.
• Validated bio-inspired hypotheses, achieving low cost-of-transport (3.33) and minimal leg slippage (<10%).

Conclusions:

• The developed framework enables precise control of microrobot leg trajectories for enhanced locomotion.
• Bio-inspired trajectories significantly improve speed, reduce energy consumption, and minimize leg slippage.
• This work advances the capabilities of small legged robots for complex operating environments.