Variational inference mpc using normalizing flows and out-of-distribution projection

T Power, D Berenson - arXiv preprint arXiv:2205.04667, 2022 - arxiv.org
We propose a Model Predictive Control (MPC) method for collision-free navigation that uses
amortized variational inference to approximate the distribution of optimal control sequences …
被引用次数：20 相关文章
[PDF] archive.org

[PDF][PDF] Variational Inference MPC using Normalizing Flows and Out-of-Distribution Projection

T Power, D Berenson - scholar.archive.org
We propose a Model Predictive Control (MPC) method for collision-free navigation that uses
amortized variational inference to approximate the distribution of optimal control sequences …

Variational Inference MPC using Normalizing Flows and Out-of-Distribution Projection

T Power, D Berenson - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
Abstract We propose a Model Predictive Control (MPC) method for collision-free navigation
that uses amortized variational inference to approximate the distribution of optimal control …
[PDF] roboticsproceedings.org

[PDF][PDF] Variational Inference MPC using Normalizing Flows and Out-of-Distribution Projection

T Power, D Berenson - roboticsproceedings.org
We propose a Model Predictive Control (MPC) method for collision-free navigation that uses
amortized variational inference to approximate the distribution of optimal control sequences …
[PDF] nsf.gov

[PDF][PDF] Variational Inference MPC using Normalizing Flows and Out-of-Distribution Projection

T Power, D Berenson - Robotics: Science and Systems 2022., 2022 - par.nsf.gov
We propose a Model Predictive Control (MPC) method for collision-free navigation that uses
amortized variational inference to approximate the distribution of optimal control sequences …
[PDF] nsf.gov

[PDF][PDF] Variational Inference MPC using Normalizing Flows and Out-of-Distribution Projection

T Power, D Berenson - Robotics science and systems, 2023 - par.nsf.gov
We propose a Model Predictive Control (MPC) method for collision-free navigation that uses
amortized variational inference to approximate the distribution of optimal control sequences …