Informationally Decoupled Trajectory Design for Sim-to-Real System Identification
The Informationally Decoupled Trajectory Design (IDTD) framework improves parameter estimation in sampling-based system identification by designing exploration trajectories that ensure each physical parameter has a unique effect. It uses a normalized Schur complement score from the Fisher information matrix to select trajectory segments that expose distinct parameter subsets, leading to significantly better sim-to-real transfer across various robots.