Double loop control strategy with different time steps based on human characteristics.

Area of Science:

• Robotics
• Human-Robot Interaction
• Control Systems

Background:

• Human-robot interaction requires control strategies that account for human physical limitations and sensor noise.
• Existing methods may not adequately address the dynamic nature of human force sensitivity and sensor feedback.

Purpose of the Study:

• To propose and evaluate a cooperative control strategy for physical human-robot interaction.
• To investigate the impact of variable sampling times in the intention estimation loop on cooperative control performance.
• To address challenges posed by human force sensitivity and noisy sensor data.

Main Methods:

• A two-loop control strategy was developed: a variable-sampling-time intention estimation loop and a fixed-time-step position control loop.
• Experiments involved a two-degree-of-freedom robot performing pull-and-push tasks.
• The norm of interaction forces was measured to quantify cooperative control performance across different sampling times.

Main Results:

• The study identified suitable sampling times for the intention estimation loop in physical human-robot interaction.
• Variable sampling times in the intention estimation loop were shown to be effective.
• The proposed strategy demonstrated measurable cooperative control performance.

Conclusions:

• Optimizing sampling times for intention estimation is crucial for effective cooperative control in human-robot interaction.
• The developed strategy offers a viable approach to enhance physical human-robot collaboration.
• Further research can explore adaptive control mechanisms for more robust interaction.