Performance analysis of autonomous UV disinfecting robot (UV bot) using Taguchi method.

Area of Science:

• Robotics
• Epidemiology
• Public Health

Background:

• The COVID-19 pandemic highlighted the need for automated disinfection solutions.
• Viral contamination poses significant public health risks, necessitating advanced sanitation technologies.
• Existing disinfection methods are often surpassed by more effective, automated alternatives.

Purpose of the Study:

• To develop an efficient and user-friendly UV-Bot for autonomous disinfection.
• To achieve a high germ clearance rate in healthcare environments.
• To integrate advanced navigation and safety features for robotic deployment.

Main Methods:

• Development of a compact, efficiently shaped UV disinfection robot (UV-Bot).
• Implementation of a custom algorithm for human detection and obstacle avoidance.
• Utilizing the A* algorithm for autonomous navigation and map retrieval of disinfection sites.
• Validation of disinfection efficacy using Taguchi analysis and 3D modeling.

Main Results:

• The UV-Bot demonstrated a germ clearance rate of up to 96.8% under specific conditions.
• Autonomous navigation with human detection and obstacle avoidance capabilities were successfully implemented.
• The robot supports live streaming of disinfection sites and includes an emergency stop function.
• 3D modeling and testing confirmed the robot's effectiveness against static and dynamic obstacles.

Conclusions:

• The UV-Bot offers a highly accurate and efficient solution for viral disinfection in healthcare settings.
• Its autonomous capabilities and safety features make it suitable for deployment in hospital pathways and rooms.
• The developed robot provides a valuable tool for combating viral contamination and enhancing public health during epidemics.