41 citations · 203 across the 38 of their papers we have counts for
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cs.RO2023
Explaining the Decisions of Deep Policy Networks for Robotic Manipulations
Seongun Kim, Jaesik Choi
Deep policy networks enable robots to learn behaviors to solve various real-world complex tasks in an end-to-end fashion. However, they lack transparency to provide the reasons of…
cs.RO2023
Adaptive and Explainable Deployment of Navigation Skills via Hierarchical Deep Reinforcement Learning
Kyowoon Lee, Seongun Kim, Jaesik Choi
For robotic vehicles to navigate robustly and safely in unseen environments, it is crucial to decide the most suitable navigation policy. However, most existing deep reinforcement…
cs.RO2016★ 1 cited
An End-to-End Robot Architecture to Manipulate Non-Physical State Changes of Objects
Wonjun Yoon, Sol-A Kim, Jaesik Choi
With the advance in robotic hardware and intelligent software, humanoid robot plays an important role in various tasks including service for human assistance and heavy job for haza…