3 papers
cs.RO2025
C2F-Space: Coarse-to-Fine Space Grounding for Spatial Instructions using Vision-Language Models
Nayoung Oh, Dohyun Kim, Junhyeong Bang +2
Space grounding refers to localizing a set of spatial references described in natural language instructions. Traditional methods often fail to account for complex reasoning -- such…
cs.RO2025
ILCL: Inverse Logic-Constraint Learning from Temporally Constrained Demonstrations
Minwoo Cho, Jaehwi Jang, Daehyung Park
We aim to solve the problem of temporal-constraint learning from demonstrations to reproduce demonstration-like logic-constrained behaviors. Learning logic constraints is challengi…
cs.RO2025
Implicit Neural-Representation Learning for Elastic Deformable-Object Manipulations
Minseok Song, JeongHo Ha, Bonggyeong Park +1
We aim to solve the problem of manipulating deformable objects, particularly elastic bands, in real-world scenarios. However, deformable object manipulation (DOM) requires a policy…