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Multi-Shooting Differential Dynamic Programming for Hybrid Systems using Analytical Derivatives

Robotics 2023-07-25 v1

Abstract

Differential Dynamic Programming (DDP) is a popular technique used to generate motion for dynamic-legged robots in the recent past. However, in most cases, only the first-order partial derivatives of the underlying dynamics are used, resulting in the iLQR approach. Neglecting the second-order terms often slows down the convergence rate compared to full DDP. Multi-Shooting is another popular technique to improve robustness, especially if the dynamics are highly non-linear. In this work, we consider Multi-Shooting DDP for trajectory optimization of a bounding gait for a simplified quadruped model. As the main contribution, we develop Second-Order analytical partial derivatives of the rigid-body contact dynamics, extending our previous results for fixed/floating base models with multi-DoF joints. Finally, we show the benefits of a novel Quasi-Newton method for approximating second-order derivatives of the dynamics, leading to order-of-magnitude speedups in the convergence compared to the full DDP method.

Keywords

Cite

@article{arxiv.2307.12606,
  title  = {Multi-Shooting Differential Dynamic Programming for Hybrid Systems using Analytical Derivatives},
  author = {Shubham Singh and Ryan P. Russell and Patrick M. Wensing},
  journal= {arXiv preprint arXiv:2307.12606},
  year   = {2023}
}

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https://www.youtube.com/watch?v=C0h6mEpcnAE

R2 v1 2026-06-28T11:38:24.566Z