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Area-Coverage Planning for Spray-based Surface Disinfection with a Mobile Manipulator.

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Robots enhance disinfection against contagious diseases by autonomously planning spray paths for mobile manipulators. This algorithm ensures thorough surface coverage and minimizes disinfectant waste, improving safety and efficiency.

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Area of Science:

  • Robotics and Automation
  • Infectious Disease Control
  • Surface Science

Background:

  • Robots are increasingly vital in combating highly contagious diseases like SARS-COV-2, Ebola, and MERS.
  • Manual disinfection is labor-intensive, risky, and prone to human error, especially in critical areas.

Purpose of the Study:

  • To develop an area-coverage planning algorithm for autonomous mobile manipulators to disinfect surfaces.
  • To ensure thorough disinfection by optimizing spray paths and disinfectant delivery.

Main Methods:

  • Projecting point clouds of surfaces onto a plane to create polygons.
  • Utilizing a branch and bound-based tree search for area coverage and spray path generation.
  • Employing successive refinement for mobile manipulator trajectory optimization and joint velocity regulation.

Main Results:

  • The developed algorithm efficiently covers polygonal areas, generating optimal spray paths.
  • The system ensures adequate disinfectant application to all surface points.
  • Simulations demonstrated superior efficiency in area coverage and reduced disinfectant wastage compared to competing methods.

Conclusions:

  • The proposed area-coverage planning algorithm enables effective and efficient robotic surface disinfection.
  • Optimized path planning and motion control are crucial for thorough disinfection and minimizing resource use.
  • The ADAMMS-SD system shows promise for autonomous disinfection in healthcare and other high-risk environments.