Optimizing UVC Disinfection Robot Navigation
Author Information
Author(s): Peñacoba Mario, Bayona Eduardo, Sierra-García Jesús Enrique, Santos Matilde
Primary Institution: Department of Digitalization, University of Burgos, Spain
Hypothesis
Can bio-inspired algorithms improve the navigation efficiency of UVC disinfection robots in complex environments?
Conclusion
The study demonstrates that bio-inspired algorithms can significantly enhance the navigation and disinfection efficiency of mobile robots in various environments.
Supporting Evidence
- The proposed algorithms effectively adapt the robot’s trajectory to various environments.
- Experimental results show that the gazelle optimization algorithm outperformed others in simpler environments.
- The study highlights the potential of bio-inspired algorithms to improve automatic disinfection.
- UVC disinfection is effective against pathogens like SARS-CoV-2.
Takeaway
This study shows how robots can clean surfaces using special lights by following smart paths inspired by animals, making them better at avoiding obstacles and reaching all areas.
Methodology
The study applied four bio-inspired algorithms (GOA, WOA, BA, PSO) to optimize the trajectories of a UVC disinfection robot in complex environments.
Limitations
The whale optimization algorithm struggled in complex environments, often getting stuck in local minima.
Digital Object Identifier (DOI)
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