Multi-Shooting Differential Dynamic Programming for Hybrid Systems using Analytical Derivatives
Singh, Shubham, Russell, Ryan P., Wensing, Patrick M.
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Jul-24-2023
- Country:
- Europe > France
- Occitanie > Haute-Garonne > Toulouse (0.04)
- North America > United States
- Indiana > St. Joseph County
- Notre Dame (0.04)
- Texas > Travis County
- Austin (0.14)
- Indiana > St. Joseph County
- Europe > France
- Genre:
- Research Report (0.40)
- Technology: