23 citations · 80 across the 17 of their papers we have counts for
5 papers · 1 filter
Multiscale Inverse Reinforcement Learning using Diffusion Wavelets
Jung-Su Ha, Han-Lim Choi
This work presents a multiscale framework to solve an inverse reinforcement learning (IRL) problem for continuous-time/state stochastic systems. We take advantage of a diffusion wa…
Informative Path Planning and Mapping with Multiple UAVs in Wind Fields
Doo-Hyun Cho, Jung-Su Ha, Sujin Lee +2
Informative path planning (IPP) is used to design paths for robotic sensor platforms to extract the best/maximum possible information about a quantity of interest while operating u…
Multiscale Abstraction, Planning and Control using Diffusion Wavelets for Stochastic Optimal Control Problems
Jung-Su Ha, Han-Lim Choi
This work presents a multiscale framework to solve a class of stochastic optimal control problems in the context of robot motion planning and control in a complex environment. In o…
Iterative Methods for Efficient Sampling-Based Optimal Motion Planning of Nonlinear Systems
Jung-Su Ha, Han-Lim Choi, Jeong hwan Jeon
This paper extends the RRT* algorithm, a recently developed but widely-used sampling-based optimal motion planner, in order to effectively handle nonlinear kinodynamic constraints.…
Topology-Guided Path Integral Approach for Stochastic Optimal Control in Cluttered Environment
Jung-Su Ha, Soon-Seo Park, Han-Lim Choi
This paper addresses planning and control of robot motion under uncertainty that is formulated as a continuous-time, continuous-space stochastic optimal control problem, by develop…