10 citations · 20 across the 9 of their papers we have counts for
7 papers · 1 filter
High-dimensional Optimal Density Control with Wasserstein Metric Matching
Shaojun Ma, Mengxue Hou, Xiaojing Ye +1
We present a novel computational framework for density control in high-dimensional state spaces. The considered dynamical system consists of a large number of indistinguishable age…
Optimal control for stochastic nonlinear Schrodinger equation on graph
Jianbo Cui, Shu Liu, Haomin Zhou
We study the optimal control formulation for stochastic nonlinear Schrodinger equation (SNLSE) on a finite graph. By viewing the SNLSE as a stochastic Wasserstein Hamiltonian flow…
Wasserstein Hamiltonian flow with common noise on graph
Jianbo Cui, Shu Liu, Haomin Zhou
We study the Wasserstein Hamiltonian flow with a common noise on the density manifold of a finite graph. Under the framework of stochastic variational principle, we first develop t…
Path Planning in Unknown Environments Using Optimal Transport Theory
Haoyan Zhai, Magnus Egerstedt, Haomin Zhou
This paper introduces a graph-based, potential-guided method for path planning problems in unknown environments, where obstacles are unknown until the robots are in close proximity…
Collective motion planning for a group of robots using intermittent diffusion
Christina Frederick, Magnus Egerstedt, Haomin Zhou
In this work we establish a simple yet effective strategy, based on optimal transport theory, for enabling a group of robots to accomplish complex tasks, such as shape formation an…
Parametric Fokker-Planck equation
Wuchen Li, Shu Liu, Hongyuan Zha +1
We derive the Fokker-Planck equation on the parametric space. It is the Wasserstein gradient flow of relative entropy on the statistical manifold. We pull back the PDE to a finite…