9 papers
Sling2Sim2Real: One-Shot Elastic System Identification for Non-Destructive Slingshot Policy Learning
Wonjae Kang, Geonwoo Kim, Minseok Song +1
Elastic object manipulation (EOM) involves highdimensional, nonlinear, and elastic deformations. The diverse deformation properties of elastic objects substantially expand the rele…
ParCo-SDF: Learning Prior-Free Partial-to-Complete Signed Distance Fields of Deformable Objects
Deokmin Hwang, Minseok Song, Daehyung Park
This study addresses the partial-to-complete geometry reconstruction of deformable objects (DOs) from point-cloud observations toward precise DO manipulation. Recent DO reconstruct…
SuReNav: Superpixel Graph-based Constraint Relaxation for Navigation in Over-constrained Environments
Keonyoung Koh, Moonkyeong Jung, Samuel Seungsup Lee +1
We address the over-constrained planning problem in semi-static environments. The planning objective is to find a best-effort solution that avoids all hard constraint regions while…
Dynamic Full-body Motion Agent with Object Interaction via Blending Pre-trained Modular Controllers
Sanghyeok Nam, Byoungjun Kim, Daehyung Park +1
Generating physically plausible dynamic motions of human-object interaction (HOI) remains challenging, mainly due to existing HOI datasets limited to static interactions, and pretr…
A Visuo-Tactile Data Collection System with Haptic Feedback for Coarse-to-Fine Imitation Learning
Yeseung Kim, Nayoung Oh, Jun Park +2
We present a visuo-tactile data-collection system that generates temporally structured, contact-rich demonstrations for imitation learning. Conventional systems often decouple the…
DiSPo: Diffusion-SSM based Policy Learning for Coarse-to-Fine Action Discretization
Nayoung Oh, Jaehyeong Jang, Moonkyeong Jung +1
We aim to solve the problem of generating coarse-to-fine skills learning from demonstrations (LfD). To scale precision, traditional LfD approaches often rely on extensive fine-grai…