Adaptive Robotic Disinfection for Targeted Surface Decontamination
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Solution Overview
Problem
Conventional methods for disinfecting built environments are labor-intensive, time-consuming, and pose health risks to workers, as pathogens can persist on surfaces for extended periods and spread quickly, necessitating an automated and adaptive robotic disinfection solution.
Innovation Solution
A computer-implemented method using a machine learning-based classifying algorithm to identify potentially contaminated surfaces and calculate trajectories for a robotic disinfectant to effectively target and disinfect these areas, integrating SLAM techniques for navigation and object affordance mapping to ensure precise and efficient disinfection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual cleaning and disinfection is used, then workers can directly clean surfaces, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent replaces manual mechanical cleaning with an automated robotic system that uses UV-C light for disinfection. The robotic device autonomously navigates through the environment, identifies contaminated surfaces using computer vision, and applies UV-C irradiation without human intervention, thereby eliminating labor-intensive manual cleaning processes and reducing disinfection time.
Solution Approach 2:
The robotic disinfection system performs self-navigation, self-localization, and self决策-making through integrated sensors and algorithms. The robot independently identifies contaminated surfaces, plans its movement trajectory, and executes disinfection without requiring human operators to guide each action, enabling autonomous operation that improves productivity while reducing time loss.
2Reliability
If frequent manual disinfection is performed, then pathogen transmission can be reduced, but worker health risks increase due to exposure to chemicals and devices
Solution Approach 1:
The patent replaces chemical disinfectants and manual cleaning devices with UV-C light-based disinfection. This substitution eliminates worker exposure to harmful chemicals and physical devices while maintaining effective pathogen prevention through photodisinfection, thereby reducing health risks while preserving reliability.
Solution Approach 2:
The robotic system acts as an intermediary between the disinfection source and the environment, delivering UV-C irradiation to contaminated surfaces without requiring human workers to be present in the immediate vicinity. This intermediary approach maintains effective pathogen prevention while protecting worker health by eliminating direct exposure.
3Productivity
If automated robotic disinfection is implemented, then worker safety improves and disinfection efficiency increases, but the system complexity increases
Solution Approach 1:
The robotic disinfection system integrates multiple functions into a single platform: navigation, surface identification, trajectory planning, and UV-C disinfection. By combining these functions in one universal device, the system achieves high productivity while managing complexity through functional integration rather than requiring separate systems for each task.
Solution Approach 2:
The patent merges computer vision algorithms, SLAM navigation, trajectory optimization, and UV-C irradiation delivery into a single integrated robotic system. This consolidation of multiple subsystems into one unified platform improves disinfection efficiency while containing overall system complexity through coordinated integration.
4Reliability
If comprehensive surface disinfection is performed, then pathogen spread is reduced, but the time and resources required increase significantly
Solution Approach 1:
The patent applies disinfection resources selectively to locally identified contaminated surfaces rather than uniformly treating all surfaces. The computer vision system identifies specific high-risk areas, and the robotic device concentrates UV-C irradiation on these localized regions, thereby maintaining effective pathogen prevention while reducing overall disinfection time and resource consumption.
Solution Approach 2:
The system performs preliminary identification and mapping of contaminated surfaces before executing disinfection. By pre-segmenting the environment and locating high-risk areas in advance, the robotic device can optimize its trajectory and focus disinfection efforts on critical surfaces, reducing the time required for comprehensive pathogen prevention.
Data Source
AI summary
Provided are methods and apparatus for environment-adaptive robotic disinfecting. In an example, provided is a method that can include (i) creating, from digital images, a map of a structure; (ii) identifying a location of a robot in the structure; (iii) segmenting, using a machine learning-based classifying algorithm trained based on object affordance information, the digital images to identify potentially contaminated surfaces within the structure; (iv) creating a map of potentially contaminated surfaces within the structure; (v) calculating a trajectory of movement of the robot to move the robot to a location of a potentially contaminated surface in the potentially contaminated surfaces; and (vi) moving the robot along the trajectory of movement to position a directional decontaminant source adjacent to the potentially contaminated surface. Other methods, systems, and computer-readable media are also disclosed.