Revised Control Barrier Function with Sensing of Threats from Relative Velocity Between Humans and Mobile Robots

Area of Science:

• Robotics and Automation
• Human-Robot Interaction
• Control Systems Engineering

Background:

• Mobile robots in industrial automation face safety challenges due to unpredictable human movement.
• Existing safe control methods struggle with real-time threat identification in dense human-robot environments.
• Ensuring safety is critical for the widespread adoption of collaborative robots.

Purpose of the Study:

• To develop an advanced safe control framework for mobile robots operating alongside humans.
• To enhance the real-time identification of potential collision threats posed by human proximity and motion.
• To improve the safety and efficiency of human-mobile robot coexistence in industrial automation.

Main Methods:

• A kinematic-based safe control framework was established for mobile robots.
• Convex programming with parametric description of skew line segments was employed to efficiently calculate human-robot proximity.
• A novel threatening index was developed, utilizing relative velocity and common normal vectors to identify critical human body parts.
• The threatening index was integrated into the safety constraint for improved control performance.

Main Results:

• The proposed method efficiently calculates proximity between human and robot components without case-by-case spatial pose analysis.
• The novel threatening index effectively identifies the most vulnerable human parts based on dynamic interactions.
• Simulations demonstrated improved safe control performance in human-mobile robot coexistence scenarios.
• The framework addresses limitations of existing methods in detecting fast relative motions.

Conclusions:

• The developed safe control framework enhances mobile robot safety in human-populated industrial environments.
• The novel threatening index and proximity calculation method offer a more robust approach to human-robot interaction safety.
• This research contributes to safer and more efficient industrial automation through improved human-robot collaboration.