5 papers
Flow-Matched Motion Priors: Online Optimal-Transport Rewards for Imitation Learning
Yilin Zou, Chenghua Liu, Chenglong Wu +1
Learning a motion prior requires a reward that guides a policy from its current behavior toward demonstrated motion. Adversarial Motion Priors (AMP) provide such a reward with a di…
Parallel-in-Time Nonlinear Optimal Control via GPU-native Sequential Convex Programming
Yilin Zou, Zhong Zhang, Maxime Robic +1
Real-time solution of nonlinear optimal control problems remains challenging on embedded robotic hardware, where conventional solvers often rely on global sparse linear algebra or…
Re-examining the Legendre-Gauss-Lobatto Pseudospectral Methods for Optimal Control
Yilin Zou, Fanghua Jiang
Pseudospectral methods represent an efficient approach for solving optimal control problems. While Legendre-Gauss-Lobatto (LGL) collocation points have traditionally been considere…
Multi-Revolution Low-Thrust Trajectory Optimization With Very Sparse Mesh Pseudospectral Method
Yilin Zou, Fanghua Jiang
Multi-revolution low-thrust trajectory optimization problems are important and challenging in space mission design. In this paper, an efficient, accurate, and widely applicable pse…
Vectorized Sparse Second-Order Forward Automatic Differentiation for Optimal Control Direct Methods
Yilin Zou, Fanghua Jiang
Direct collocation methods are widely used numerical techniques for solving optimal control problems. The discretization of continuous-time optimal control problems transforms them…