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Results 1-9 of 9 (Search time: 0.006 seconds).

NO Title, Author(s) (Publication Title, Volume Issue, Page, Issue Date)
1
Topology-guided path integral approach for stochastic optimal control in cluttered environment

Ha, Jung-Su; Park, Soon-Seo; Choi, Han-Lim, ROBOTICS AND AUTONOMOUS SYSTEMS, v.113, pp.81 - 93, 2019-03

2
A Quadratic-Cost Dual Control-Based Approach for Optimal Trajectory Planning under Uncertainty

Kim, Jinwhan; Ha, Jung-Su; Choi, Han-Lim, INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, v.15, no.5, pp.2253 - 2261, 2017-10

3
ITERATIVE METHODS FOR EFFICIENT SAMPLING-BASED OPTIMAL MOTION PLANNING OF NONLINEAR SYSTEMS

Ha, Jung-Su; Choi, Han-Lim; Jeon, Jeong Hwan, INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE, v.28, no.1, pp.155 - 168, 2018-03

4
Informative windowed forecasting of continuous-time linear systems for mutual information-based sensor planning

Choi, Han-Lim; Ha, Jung-Su, AUTOMATICA, v.57, pp.97 - 104, 2015-07

5
A Stochastic Game-Based Approach for Multiple Beyond-Visual-Range Air Combat

Ha, Jung-Su; Chae, Hyeok-Joo; Choi, Han-Lim, UNMANNED SYSTEMS, v.6, no.1, pp.67 - 79, 2018-01

6
A Distributed ADMM Approach to Non-Myopic Path Planning for Multi-Target Tracking

Park, Soon-Seo; Min, Youngjae; Ha, Jung-Su; Cho, Doo-Hyun; Choi, Han-Lim, IEEE ACCESS, v.7, pp.163589 - 163603, 2019-11

7
On periodic optimal solutions of persistent sensor planning for continuous-time linear systems

Ha, Jung-Su; Choi, Han-Lim, AUTOMATICA, v.99, pp.138 - 148, 2019-01

8
Approximate Inference-Based Motion Planning by Learning and Exploiting Low-Dimensional Latent Variable Models

Ha, Jung-Su; Chae, Hyeok-Joo; Choi, Han-Lim, IEEE ROBOTICS AND AUTOMATION LETTERS, v.3, no.4, pp.3892 - 3899, 2018-10

9
Adaptive path-integral autoencoder: representation learning and planning for dynamical systems

Ha, Jung-Su; Park, Young Jin; Chae, Hyeok-Joo; Park, Soon-Seo; Choi, Han-Lim, JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT, v.2019, no.12, 2019-12

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