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

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.