rpd-512/FORGE: FORGE v1.0

FORGE (Formation of Optimized Robotic Ground-Truth Examples) is a framework for generating high-quality, physically consistent ground-truth datasets for robotic systems. It integrates forward kinematics, collision-aware evaluation, and metaheuristic optimization to identify robot configurations that minimize positional error and angular deviation.

The framework is designed to support data-driven approaches to inverse kinematics, enabling the creation of large-scale, reliable datasets for training and evaluating machine learning models. FORGE is modular, extensible, and suitable for a wide range of robotic manipulators and optimization strategies.