3 papers
cs.RO2026
Function-Space Diffusion for Motion Planning
Zinuo Chang, Yipu Chen, Byoungwoo Park +2
Diffusion-based motion planners have demonstrated strong performance in generating diverse and high-quality robot trajectories in cluttered environments with multiple feasible solu…
cs.RO2026
PISTO: Proximal Inference for Stochastic Trajectory Optimization
Hongzhe Yu, Zinuo Chang, Yongxin Chen
Stochastic trajectory optimization methods like STOMP enable planning with non-differentiable costs, offering substantial flexibility over gradient-based approaches. We show that S…
cs.RO2025
Efficient Iterative Proximal Variational Inference Motion Planning
Zinuo Chang, Hongzhe Yu, Patricio Vela +1
We cast motion planning under uncertainty as a stochastic optimal control problem, where the optimal posterior distribution has an explicit form. To approximate this posterior, thi…