Jung-Su Ha

IEEE Robotics Autom. Lett., 2022

Sequence-of-Constraints MPC: Reactive Timing-Optimal Control of Sequential Manipulation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021

A diffusion wavelets-based multiscale framework for inverse optimal control of stochastic systems.

[BibT_eX]

[DOI]

Int. J. Syst. Sci., 2021

Learning to solve sequential physical reasoning problems from a scene image.

[BibT_eX]

[DOI]

Int. J. Robotics Res., 2021

Learning Neural Implicit Functions as Object Representations for Robotic Manipulation.

[BibT_eX]

[DOI]

CoRR, 2021

Co-Optimizing Robot, Environment, and Tool Design via Joint Manipulation Planning.

[BibT_eX]

[DOI]

Ozgur S. Oguz

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Learning Geometric Reasoning and Control for Long-Horizon Tasks from Visual Input.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Structured deep generative models for sampling on constraint manifolds in sequential manipulation.

[BibT_eX]

[DOI]

Joaquim Ortiz de Haro

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Describing Physics For Physical Reasoning: Force-Based Sequential Manipulation Planning.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2020

Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XVI, 2020

A Probabilistic Framework for Constrained Manipulations and Task and Motion Planning under Uncertainty.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Deep Visual Heuristics: Learning Feasibility of Mixed-Integer Programs for Manipulation Planning.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019

Topology-guided path integral approach for stochastic optimal control in cluttered environment.

[BibT_eX]

[DOI]

Soon-Seo Park

Robotics Auton. Syst., 2019

On periodic optimal solutions of persistent sensor planning for continuous-time linear systems.

[BibT_eX]

[DOI]

Autom., 2019

A Distributed ADMM Approach to Non-Myopic Path Planning for Multi-Target Tracking.

[BibT_eX]

[DOI]

IEEE Access, 2019

2018

A Stochastic Game-Based Approach for Multiple Beyond-Visual-Range Air Combat.

[BibT_eX]

[DOI]

Unmanned Syst., 2018

Approximate Inference-Based Motion Planning by Learning and Exploiting Low-Dimensional Latent Variable Models.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2018

A Distributed ADMM Approach to Informative Trajectory Planning for Multi-Target Tracking.

[BibT_eX]

[DOI]

CoRR, 2018

Adaptive Path-Integral Approach to Representation Learning and Planning for Dynamical Systems.

[BibT_eX]

[DOI]

CoRR, 2018

Iterative methods for efficient sampling-based optimal motion planning of nonlinear systems.

[BibT_eX]

[DOI]

Jeong hwan Jeon

Int. J. Appl. Math. Comput. Sci., 2018

Adaptive Path-Integral Autoencoders: Representation Learning and Planning for Dynamical Systems.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Adaptive Path-Integral Approach for Representation Learning and Planning.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

High-dimensional Motion Planning using Latent Variable Models via Approximate Inference.

[BibT_eX]

[DOI]

CoRR, 2017

Multiscale abstraction, planning and control using diffusion wavelets for stochastic optimal control problems.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

2016

Asymptotically Optimal Sampling-Based Algorithms for Topological Motion Planning.

[BibT_eX]

[DOI]

Soon-Seo Park

CoRR, 2016

Multiscale Inverse Reinforcement Learning using Diffusion Wavelets.

[BibT_eX]

[DOI]

CoRR, 2016

A topology-guided path integral approach for stochastic optimal control.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Informative Path Planning and Mapping with Multiple UAVs in Wind Fields.

[BibT_eX]

[DOI]

Proceedings of the Distributed Autonomous Robotic Systems, 2016

2015

An Efficient Path Integral Approach for Stochastic Optimal Control with a Topology-Embedded Sampling-Based Planner.

[BibT_eX]

[DOI]

CoRR, 2015

Informative windowed forecasting of continuous-time linear systems for mutual information-based sensor planning.

[BibT_eX]

[DOI]

Autom., 2015

A stochastic game-theoretic approach for analysis of multiple cooperative air combat.

[BibT_eX]

[DOI]

Proceedings of the American Control Conference, 2015

2014

Periodic sensing trajectory generation for persistent monitoring.

[BibT_eX]

[DOI]

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

2013

A successive approximation-based approach for optimal kinodynamic motion planning with nonlinear differential constraints.

[BibT_eX]

[DOI]

Ju-Jang Lee