HeSARIC: A Heterogeneous Cyber-Physical Robotic Swarm Framework for Structural Health Monitoring with Augmented...

Area of Science:

• Robotics and Automation
• Cyber-Physical Systems
• Structural Health Monitoring

Background:

• Confined space inspection and structural health monitoring present unique challenges.
• Existing methods often lack the flexibility and comprehensive data acquisition needed for complex structures.

Purpose of the Study:

• To propose a novel cyber-physical framework, HeSARIC, for integrating heterogeneous robotic systems and augmented reality.
• To enhance structural health monitoring and confined space inspection capabilities.

Main Methods:

• Development of a heterogeneous robot swarm including robots, sensors, and microrobots.
• Integration of augmented reality (AR) and PC interfaces for human-robot collaboration and teleoperation.
• Application of edge computing and machine learning for enhanced operator interaction and damage detection.

Main Results:

• Demonstrated framework for effective integration of diverse robotic agents.
• Improved human-robot collaboration through intuitive AR and PC interfaces.
• Enhanced accuracy in detecting structural damages like cracks and deformations in confined spaces.

Conclusions:

• The HeSARIC framework offers a robust solution for complex structural inspection tasks.
• The integration of swarm robotics, AR, and edge AI significantly improves monitoring and inspection efficiency.
• This approach addresses critical challenges in structural health monitoring and confined space exploration.