A new generation of autonomous UV-C disinfection robots is showing promise in transforming how hospitals maintain sterile environments. Developed by a research team at Pohang University of Science and Technology (POSTECH) in South Korea, this innovative technology integrates intelligent path planning, real-time environmental awareness, and deep learning to achieve comprehensive room disinfection without human intervention.

Addressing a Persistent Healthcare Challenge

Healthcare-associated infections (HAIs) remain a significant threat in medical facilities worldwide. While manual cleaning and disinfection methods are the standard, they are labor-intensive and often inconsistent, especially in complex environments with high patient turnover and frequent contact surfaces. Although effective in killing pathogens, traditional UV-C systems typically require manual operation or follow pre-programmed static routes that fail to account for real-time changes in room configuration or human movement.

Recognizing these limitations, the POSTECH team set out to build a robotic system capable of making intelligent decisions about where, how, and when to disinfect, based on its assessment of its environment. The result is a robot that not only navigates autonomously but also adapts its behaviour dynamically using artificial intelligence and sensor feedback.

Engineering Autonomy into Action

The robot uses high-resolution vision sensors and LIDAR to construct a real-time map of its surroundings. Through embedded deep learning algorithms, it can detect potential obstacles, avoid human presence, and identify high-contact surfaces that require focused disinfection. The UV-C lamps, known for their effectiveness in neutralising bacteria and viruses, are activated based on the robot’s continuously updated risk map.

A particularly novel feature is the robot’s ability to replan its route autonomously if a person enters the space mid-cycle. Unlike traditional robots, which would require restarting the disinfection cycle from the beginning, this system recalculates remaining coverage areas and adjusts its movements to continue disinfection efficiently.

Initial trials in simulated hospital rooms demonstrated the robot’s ability to achieve nearly 100% surface coverage, including hard-to-reach corners and areas often missed by manual cleaning or stationary UV-C systems.

Expanding Potential Beyond Hospitals

While developed for healthcare settings, the technology has wider relevance. High-traffic environments like airports, public transport systems, schools, and food-processing facilities could benefit from automated, intelligent sterilization methods. The ability to perform targeted disinfection autonomously and safely—even while people are present—offers a major advantage in high-demand sectors with stringent hygiene requirements.

According to the researchers, the long-term vision includes deploying fleets of such robots that can coordinate with each other, monitor infection patterns, and optimize cleaning schedules across entire facilities.

A Systems Engineering Perspective

This breakthrough reflects the power of systems engineering to integrate diverse technologies like mechanical design, embedded electronics, control systems, computer vision, and AI into a cohesive, high-functioning system that performs reliably in real-world, variable environments.

From a systems perspective, the robot embodies:

• Real-Time Data Fusion and Feedback Control: Integrating live sensor input with AI-driven decision-making supports adaptive operation and resilience.
• Modular and Scalable Architecture: The system’s design enables ease of updates, hardware replacement, and future extensions, such as swarm behavior or remote fleet management.
• Human-System Interaction Design: Safety and efficiency are enhanced through the robot’s ability to detect and respond to human presence without compromising performance.
• Operational Readiness in Complex Environments: This case demonstrates how systems thinking enables solutions that must function under unpredictability, variability, and regulatory constraints.

At Project Performance International (PPI), we emphasize the application of systems engineering in solving high-stakes, real-world problems. This robot is a clear example of how rigorous systems integration and lifecycle thinking can address complex challenges, in this case, enhancing public health infrastructure through intelligent automation.

References

Pohang University of Science & Technology (POSTECH) 2025, ‘ Transforming Hospital Sanitation: Autonomous Robots for Wiping and UV-C Disinfection’, Pohang University of Science and Technology, viewed 8 May 2025, <https://www.postech.ac.kr/eng/research/research_results.do?mode=view&articleNo=18344&article.offset=0&articleLimit=10>

Life Technology 2025, ‘Intelligent Autonomous UV-C Disinfection Robot For Hospitals’, Life Technology, viewed 8 May 2025, <https://www.lifetechnology.com/blogs/life-technology-technology-news/intelligent-autonomous-uv-c-disinfection-robot-for-hospitals>

Pohang University of Science & Technology (POSTECH) 2025, ‘Transforming hospital sanitation: Autonomous robots for wiping and UV-C disinfection’, ScienceDaily, viewed 8 May 2025, <www.sciencedaily.com/releases/2025/05/250507130744.htm>