Surface Coverage

Surface coverage optimization focuses on efficiently and effectively monitoring or imaging a target area, whether a physical object, a geographical region, or data points in a high-dimensional space. Current research emphasizes developing algorithms, such as expectation-maximization, spectral clustering, and improved metaheuristics like wolf pack algorithms, to strategically plan viewpoints or sensor placements for maximizing coverage while minimizing resource consumption. These advancements are crucial for diverse applications ranging from efficient 3D modeling and building inspection using drones to optimizing satellite data analysis and improving the performance of deep learning models by ensuring comprehensive testing.