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ORCIDJung-Su Ha
- > Home > Persons > Jung-Su Ha
Publications
- 2021
[j9]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): 2228-2240 (2021)- [c14]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: 4459-4466 - 2020
- [i10]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 abs/2011.08345 (2020) - 2019
- [j7]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: 163589-163603 (2019) - [j6]Jung-Su Ha, Han-Lim Choi:
On periodic optimal solutions of persistent sensor planning for continuous-time linear systems. Autom. 99: 138-148 (2019) - [j5]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: 81-93 (2019) - 2018
- [j4]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): 155-168 (2018) - [j3]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): 3892-3899 (2018) - [j2]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): 67-79 (2018) - [c8]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 - [c7]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: 8941-8952 - [i9]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 abs/1807.02128 (2018) - [i8]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 abs/1807.11068 (2018) - 2017
- [c6]Jung-Su Ha, Han-Lim Choi:
Multiscale abstraction, planning and control using diffusion wavelets for stochastic optimal control problems. ICRA 2017: 687-694 - [i7]Jung-Su Ha, Hyeok-Joo Chae, Han-Lim Choi:
High-dimensional Motion Planning using Latent Variable Models via Approximate Inference. CoRR abs/1711.08275 (2017) - 2016
- [c5]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: 269-283 - [c4]Jung-Su Ha, Han-Lim Choi:
A topology-guided path integral approach for stochastic optimal control. ICRA 2016: 4605-4612 - [i6]Jung-Su Ha, Han-Lim Choi, Jeong hwan Jeon:
Iterative Methods for Efficient Sampling-Based Optimal Motion Planning of Nonlinear Systems. CoRR abs/1603.04112 (2016) - [i5]Jung-Su Ha, Soon-Seo Park, Han-Lim Choi:
Asymptotically Optimal Sampling-Based Algorithms for Topological Motion Planning. CoRR abs/1603.05099 (2016) - [i4]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 abs/1610.01303 (2016) - [i3]Jung-Su Ha, Han-Lim Choi:
Multiscale Abstraction, Planning and Control using Diffusion Wavelets for Stochastic Optimal Control Problems. CoRR abs/1610.06819 (2016) - [i2]Jung-Su Ha, Han-Lim Choi:
Multiscale Inverse Reinforcement Learning using Diffusion Wavelets. CoRR abs/1611.08070 (2016) - 2015
- [j1]Han-Lim Choi, Jung-Su Ha:
Informative windowed forecasting of continuous-time linear systems for mutual information-based sensor planning. Autom. 57: 97-104 (2015) - [c3]Jung-Su Ha, Hyeok-Joo Chae, Han-Lim Choi:
A stochastic game-theoretic approach for analysis of multiple cooperative air combat. ACC 2015: 3728-3733 - [i1]Jung-Su Ha, Han-Lim Choi:
An Efficient Path Integral Approach for Stochastic Optimal Control with a Topology-Embedded Sampling-Based Planner. CoRR abs/1510.05344 (2015) - 2014
- [c2]Jung-Su Ha, Han-Lim Choi:
Periodic sensing trajectory generation for persistent monitoring. CDC 2014: 1880-1886 - 2013
- [c1]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: 3623-3628
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