Core Concepts
The author presents a new symmetric stair preconditioner for parallel trajectory optimization, demonstrating improved performance compared to existing methods through theoretical analysis and numerical experiments.
Abstract
The content introduces a new symmetric stair preconditioner for parallel trajectory optimization, highlighting its advantages over existing methods. Theoretical properties and practical benefits are discussed, showing significant reductions in condition number and iterations needed for convergence. Numerical results validate the effectiveness of the proposed preconditioner across various trajectory optimization tasks.
Stats
Our symmetric stair preconditioner provides up to a 34% reduction in condition number.
Up to a 25% reduction in the number of resulting linear system solver iterations is achieved.