Computational Geometry and its Applications in Advanced Algorithm Design

Computational geometry improves numerous processes. Mathematics and computer science underpin this strategy. This abstract discusses computational geometry's importance and how it may address new math challenges. Geometric notions are employed in numerous ways to constrain space. Examples include Delaunay triangulation, convex Hull techniques, spatial splitting, and Voronoi diagrams. Some line overlap methods can find multidimensional data. This may be utilized in R-tree spatial sorting and CAD. Robotics and shape analysis often employ form centers and medians. The proposed approach has all of these properties, making it a flexible method for problem-solving. Because of its versatility, we propose the R-tree-based technique. People are continually creating and discovering new algorithms in computational geometry. This method can teach geography, build robots, and advance technology.