2 papers
cs.RO2025
Modality-Augmented Fine-Tuning of Foundation Robot Policies for Cross-Embodiment Manipulation on GR1 and G1
Junsung Park, Hogun Kee, Songhwai Oh
This paper presents a modality-augmented fine-tuning framework designed to adapt foundation robot policies to diverse humanoid embodiments. We validate our approach across two dist…
cs.RO2025
Tidiness Score-Guided Monte Carlo Tree Search for Visual Tabletop Rearrangement
Hogun Kee, Wooseok Oh, Minjae Kang +2
In this paper, we present the tidiness score-guided Monte Carlo tree search (TSMCTS), a novel framework designed to address the tabletop tidying up problem using only an RGB-D came…