activity
20192022
most citedDHRL: A Graph-Based Approach for Long-Horizon and Sparse Hierarchical Reinforcement Learning

3 citations · 5 across the 5 of their papers we have counts for

collaborators

6 papers

cs.LG20223 cited

DHRL: A Graph-Based Approach for Long-Horizon and Sparse Hierarchical Reinforcement Learning

Seungjae Lee, Jigang Kim, Inkyu Jang +1

Hierarchical Reinforcement Learning (HRL) has made notable progress in complex control tasks by leveraging temporal abstraction. However, previous HRL algorithms often suffer from…

cs.RO2021

Robust and Recursively Feasible Real-Time Trajectory Planning in Unknown Environments

Inkyu Jang, Dongjae Lee, Seungjae Lee +1

Motion planners for mobile robots in unknown environments face the challenge of simultaneously maintaining both robustness against unmodeled uncertainties and persistent feasibilit…

cs.RO2021

Real-Time Motion Planning of a Hydraulic Excavator using Trajectory Optimization and Model Predictive Control

Dongjae Lee, Inkyu Jang, Jeonghyun Byun +2

Automation of excavation tasks requires real-time trajectory planning satisfying various constraints. To guarantee both constraint feasibility and real-time trajectory re-plannabil…

cs.RO2021

Stability and Robustness Analysis of Plug-Pulling using an Aerial Manipulator

Jeonghyun Byun, Dongjae Lee, Hoseong Seo +3

In this paper, an autonomous aerial manipulation task of pulling a plug out of an electric socket is conducted, where maintaining the stability and robustness is challenging due to…

cs.RO20202 cited

Fail-safe Flight of a Fully-Actuated Quadcopter in a Single Motor Failure

Seung Jae Lee, Inkyu Jang, H. Jin Kim

In this paper, we introduce a new quadcopter fail-safe flight solution that can perform the same four controllable degrees-of-freedom flight as a regular multirotor even when a sin…

eess.SY2019

Efficient Multi-Agent Trajectory Planning with Feasibility Guarantee using Relative Bernstein Polynomial

Jungwon Park, Junha Kim, Inkyu Jang +1

This paper presents a new efficient algorithm which guarantees a solution for a class of multi-agent trajectory planning problems in obstacle-dense environments. Our algorithm comb…