軌道最適化における逆動力学と順動力学の比較：直接変換法での検証
Inverse Dynamics vs. Forward Dynamics in Direct Transcription Formulations for Trajectory Optimization
剛体接触を含む系で逆動力学と順動力学の軌道最適化性能を比較し、逆動力学が収束速度・反復回数・粗い離散化への頑健性で優れることを示した。
著者: Henrique Ferrolho, Vladimir Ivan, Wolfgang Merkt, Ioannis Havoutis, Sethu Vijayakumar
分類: cs.RO, math.OC
原文アブストラクト
Benchmarks of state-of-the-art rigid-body dynamics libraries report better performance solving the inverse dynamics problem than the forward alternative. Those benchmarks encouraged us to question whether that computational advantage would translate to direct transcription, where calculating rigid-body dynamics and their derivatives accounts for a significant share of computation time. In this work, we implement an optimization framework where both approaches for enforcing the system dynamics are available. We evaluate the performance of each approach for systems of varying complexity, for domains with rigid contacts. Our tests reveal that formulations using inverse dynamics converge faster, require less iterations, and are more robust to coarse problem discretization. These results indicate that inverse dynamics should be preferred to enforce the nonlinear system dynamics in simultaneous methods, such as direct transcription.
