Towards an Optimal Footprint Based Area Coverage Strategy for a False-Ceiling Inspection Robot

Area of Science:

• Robotics
• Automation
• Infrastructure Management

Background:

• Manual false-ceiling inspection is inefficient and hazardous.
• Lightweight robots offer automated inspection but face payload limitations.
• Optimizing robot strategy is crucial for effective false-ceiling inspection.

Purpose of the Study:

• To develop an optimal functional footprint approach for automated false-ceiling inspection robots.
• To enhance inspection efficiency by minimizing missed areas and path length.
• To address payload constraints of lightweight robots in built infrastructure.

Main Methods:

• Utilized an evolutionary algorithm-based multi-objective optimization framework.
• Defined robot footprint based on camera installation parameters.
• Minimized area missed and path length during inspection planning.

Main Results:

• The optimal functional footprint approach significantly improves inspection efficiency.
• Numerical simulations demonstrated the effectiveness of the proposed method.
• Experimental validation on the Raptor robot confirmed the approach's viability.

Conclusions:

• The optimal functional footprint strategy enhances automated false-ceiling inspection.
• This approach overcomes payload limitations for lightweight inspection robots.
• The method contributes to more efficient and safer infrastructure management.