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Coverage Planning for UVC Irradiation: Robot Surface Disinfection Based on Swarm Intelligence Algorithm
Peiyao Guo1, Dekun Luo1, Yizhen Wu1
1Research Center for Optoelectronic Materials and Devices, Guangxi Key Laboratory for the Relativistic Astrophysics, School of Physical Science & Technology, Guangxi University, Nanning 530004, China.
Sensors (Basel, Switzerland)
|June 19, 2024
Summary
This study introduces a novel UV dose coverage planning framework for autonomous robots, optimizing energy use and reducing redundancy in disinfection tasks. The method enhances robotic disinfection efficiency for pathogen elimination.
Area of Science:
- Robotics and Automation
- Infectious Disease Control
- Photochemistry
Background:
- Ultraviolet (UV) radiation is a key strategy for pathogen disinfection.
- Autonomous mobile robots enhance disinfection coverage but face path planning complexities.
- High UV dosage for inactivation leads to energy inefficiency and dose redundancy.
Purpose of the Study:
- To develop an optimized UV dose coverage planning framework for robotic disinfection.
- To address energy consumption and dose redundancy challenges in large-scale disinfection.
- To improve the efficiency of autonomous mobile robots in pathogen inactivation.
Main Methods:
- Utilized a multi-objective optimization model solved with MOPSO (Multi-Objective Particle Swarm Optimization).
- Integrated a UV-C light efficiency factor into the planning framework.
- Focused on dose accumulation characteristics for optimized irradiation planning.
Main Results:
- The proposed framework effectively plans UV dose coverage, mitigating redundancy.
- Demonstrated significant reduction in energy expenditure for robotic disinfection.
- Empirical trials confirmed the model's efficacy in deactivating viruses using autonomous robots.
Conclusions:
- The novel dose coverage planning framework enhances robotic disinfection efficiency and reduces energy consumption.
- This approach optimizes UV disinfection by prioritizing dose accumulation and light efficiency.
- The study provides a viable solution for large-scale, energy-efficient robotic disinfection.
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