Developed a trilateration-based 2D location solver for the Matthew0826/NULunabotics repository, focusing on geometric modeling and numerical optimization. The solution introduced a Point class to represent coordinates and incorporated simulated error into distance calculations, reflecting real-world measurement uncertainty. Leveraging Python and the SciPy library, the solver used least squares optimization to estimate unknown positions from multiple reference points, providing both margin of error and standard deviation metrics. The implementation included a clear API and a basic usage example to facilitate integration and future extension. This work demonstrated depth in geometry, numerical analysis, and optimization, addressing precise localization challenges.