Jung-Su Ha

Publication Activity (10 Years)

Years Active: 2013-2023
Publications (10 Years): 41

Top Topics

Approximate Inference

Motion Planning

Reinforcement Learning

Top Venues

IEEE Robotics Autom. Lett.

Publications

Joaquim Ortiz de Haro, Jung-Su Ha, Danny Driess, Erez Karpas, Marc Toussaint
Learning Feasibility of Factored Nonlinear Programs in Robotic Manipulation Planning. ICRA (2023)
Marc Toussaint, Jason Harris, Jung-Su Ha, Danny Driess, Wolfgang Hönig
Sequence-of-Constraints MPC: Reactive Timing-Optimal Control of Sequential Manipulation. CoRR (2022)
Joaquim Ortiz de Haro, Jung-Su Ha, Danny Driess, Erez Karpas, Marc Toussaint
Learning Feasibility of Factored Nonlinear Programs in Robotic Manipulation Planning. CoRR (2022)
Marc Toussaint, Jason Harris, Jung-Su Ha, Danny Driess, Wolfgang Hönig
Sequence-of-Constraints MPC: Reactive Timing-Optimal Control of Sequential Manipulation. IROS (2022)
Jung-Su Ha, Danny Driess, Marc Toussaint
Deep Visual Constraints: Neural Implicit Models for Manipulation Planning From Visual Input. IEEE Robotics Autom. Lett. 7 (4) (2022)
Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae, Soon-Seo Park, Han-Lim Choi
Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning. ICRA (2021)
Marc Toussaint, Jung-Su Ha, Ozgur S. Oguz
Co-Optimizing Robot, Environment, and Tool Design via Joint Manipulation Planning. ICRA (2021)
Danny Driess, Jung-Su Ha, Russ Tedrake, Marc Toussaint
Learning Geometric Reasoning and Control for Long-Horizon Tasks from Visual Input. ICRA (2021)
Joaquim Ortiz de Haro, Jung-Su Ha, Danny Driess, Marc Toussaint
Structured deep generative models for sampling on constraint manifolds in sequential manipulation. CoRL (2021)
Danny Driess, Jung-Su Ha, Marc Toussaint
Learning to solve sequential physical reasoning problems from a scene image. Int. J. Robotics Res. 40 (12-14) (2021)
Jung-Su Ha, Hyeok-Joo Chae, Han-Lim Choi
A diffusion wavelets-based multiscale framework for inverse optimal control of stochastic systems. Int. J. Syst. Sci. 52 (11) (2021)
Jung-Su Ha, Danny Driess, Marc Toussaint
Learning Neural Implicit Functions as Object Representations for Robotic Manipulation. CoRR (2021)
Danny Driess, Jung-Su Ha, Marc Toussaint, Russ Tedrake
Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning. CoRR (2021)
Danny Driess, Jung-Su Ha, Marc Toussaint, Russ Tedrake
Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning. CoRL (2021)
Marc Toussaint, Jung-Su Ha, Danny Driess
Describing Physics For Physical Reasoning: Force-Based Sequential Manipulation Planning. IEEE Robotics Autom. Lett. 5 (4) (2020)
Jung-Su Ha, Danny Driess, Marc Toussaint
A Probabilistic Framework for Constrained Manipulations and Task and Motion Planning under Uncertainty. ICRA (2020)
Danny Driess, Jung-Su Ha, Marc Toussaint
Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image. Robotics: Science and Systems (2020)
Marc Toussaint, Jung-Su Ha, Danny Drieß
Describing Physics For Physical Reasoning: Force-based Sequential Manipulation Planning. CoRR (2020)
Jung-Su Ha, Danny Drieß, Marc Toussaint
Probabilistic Framework for Constrained Manipulations and Task and Motion Planning under Uncertainty. CoRR (2020)
Danny Drieß, Jung-Su Ha, Marc Toussaint
Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image. CoRR (2020)
Danny Driess, Ozgur Oguz, Jung-Su Ha, Marc Toussaint
Deep Visual Heuristics: Learning Feasibility of Mixed-Integer Programs for Manipulation Planning. ICRA (2020)
Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae, Soon-Seo Park, Han-Lim Choi
Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning. CoRR (2020)
Soon-Seo Park, Youngjae Min, Jung-Su Ha, Doo-Hyun Cho, Han-Lim Choi
A Distributed ADMM Approach to Non-Myopic Path Planning for Multi-Target Tracking. IEEE Access 7 (2019)
Jung-Su Ha, Soon-Seo Park, Han-Lim Choi
Topology-guided path integral approach for stochastic optimal control in cluttered environment. Robotics Auton. Syst. 113 (2019)
Jung-Su Ha, Han-Lim Choi
On periodic optimal solutions of persistent sensor planning for continuous-time linear systems. Autom. 99 (2019)
Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae, Soon-Seo Park, Han-Lim Choi
Adaptive Path-Integral Approach for Representation Learning and Planning. ICLR (Workshop) (2018)
Jung-Su Ha, Hyeok-Joo Chae, Han-Lim Choi
A Stochastic Game-Based Approach for Multiple Beyond-Visual-Range Air Combat. Unmanned Syst. 6 (1) (2018)
Jung-Su Ha, Han-Lim Choi, Jeong hwan Jeon
Iterative methods for efficient sampling-based optimal motion planning of nonlinear systems. Int. J. Appl. Math. Comput. Sci. 28 (1) (2018)
Jung-Su Ha, Hyeok-Joo Chae, Han-Lim Choi
Approximate Inference-Based Motion Planning by Learning and Exploiting Low-Dimensional Latent Variable Models. IEEE Robotics Autom. Lett. 3 (4) (2018)
Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae, Soon-Seo Park, Han-Lim Choi
Adaptive Path-Integral Autoencoders: Representation Learning and Planning for Dynamical Systems. NeurIPS (2018)
Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae, Soon-Seo Park, Han-Lim Choi
Adaptive Path-Integral Approach to Representation Learning and Planning for Dynamical Systems. CoRR (2018)
Soon-Seo Park, Jung-Su Ha, Doo-Hyun Cho, Han-Lim Choi
A Distributed ADMM Approach to Informative Trajectory Planning for Multi-Target Tracking. CoRR (2018)
Jung-Su Ha, Hyeok-Joo Chae, Han-Lim Choi
High-dimensional Motion Planning using Latent Variable Models via Approximate Inference. CoRR (2017)
Jung-Su Ha, Han-Lim Choi
Multiscale abstraction, planning and control using diffusion wavelets for stochastic optimal control problems. ICRA (2017)
Jung-Su Ha, Han-Lim Choi, Jeong hwan Jeon
Iterative Methods for Efficient Sampling-Based Optimal Motion Planning of Nonlinear Systems. CoRR (2016)
Jung-Su Ha, Han-Lim Choi
A topology-guided path integral approach for stochastic optimal control. ICRA (2016)
Jung-Su Ha, Soon-Seo Park, Han-Lim Choi
Asymptotically Optimal Sampling-Based Algorithms for Topological Motion Planning. CoRR (2016)
Jung-Su Ha, Han-Lim Choi
Multiscale Abstraction, Planning and Control using Diffusion Wavelets for Stochastic Optimal Control Problems. CoRR (2016)
Doo-Hyun Cho, Jung-Su Ha, Su-Jin Lee, Sunghyun Moon, Han-Lim Choi
Informative Path Planning and Mapping with Multiple UAVs in Wind Fields. CoRR (2016)
Jung-Su Ha, Han-Lim Choi
Multiscale Inverse Reinforcement Learning using Diffusion Wavelets. CoRR (2016)
Doo-Hyun Cho, Jung-Su Ha, Su-Jin Lee, Sunghyun Moon, Han-Lim Choi
Informative Path Planning and Mapping with Multiple UAVs in Wind Fields. DARS (2016)
Jung-Su Ha, Han-Lim Choi
An Efficient Path Integral Approach for Stochastic Optimal Control with a Topology-Embedded Sampling-Based Planner. CoRR (2015)
Han-Lim Choi, Jung-Su Ha
Informative windowed forecasting of continuous-time linear systems for mutual information-based sensor planning. Autom. 57 (2015)
Jung-Su Ha, Hyeok-Joo Chae, Han-Lim Choi
A stochastic game-theoretic approach for analysis of multiple cooperative air combat. ACC (2015)
Jung-Su Ha, Han-Lim Choi
Periodic sensing trajectory generation for persistent monitoring. CDC (2014)
Jung-Su Ha, Ju-Jang Lee, Han-Lim Choi
A successive approximation-based approach for optimal kinodynamic motion planning with nonlinear differential constraints. CDC (2013)