7 papers
Retrieve, Don't Retrain: Extending Vision Language Action Models to New Tasks at Test Time
Jeongeun Park, Juhan Park, Taekyung Kim +3
Extending a vision-language-action (VLA) policy to a new task typically requires task-specific teleoperated demonstrations and per-task fine-tuning, making adaptation costly in bot…
Natural Functional Gradients for Smooth Trajectory Optimization
Kisang Park, Chanwoo Kim, Kyungjae Lee +1
Generating collision-free and smooth motions remains a central challenge in robotic manipulation, particularly in cluttered environments and narrow passages where feasible regions…
LEGO: Latent-space Exploration for Geometry-aware Optimization of Humanoid Kinematic Design
Jihwan Yoon, Taemoon Jeong, Jeongeun Park +5
Designing robot morphologies and kinematics has traditionally relied on human intuition, with little systematic foundation. Motion-design co-optimization offers a promising path to…
Hierarchical Vision Language Action Model Using Success and Failure Demonstrations
Jeongeun Park, Jihwan Yoon, Byungwoo Jeon +6
Prior Vision-Language-Action (VLA) models are typically trained on teleoperated successful demonstrations, while discarding numerous failed attempts that occur naturally during dat…
Learning Social Navigation from Positive and Negative Demonstrations and Rule-Based Specifications
Chanwoo Kim, Jihwan Yoon, Hyeonseong Kim +9
Mobile robot navigation in dynamic human environments requires policies that balance adaptability to diverse behaviors with compliance to safety constraints. We hypothesize that in…
The Turkish Ice Cream Robot: Examining Playful Deception in Social Human-Robot Interactions
Hyeonseong Kim, Roy El-Helou, Seungbeen Lee +2
Playful deception, a common feature in human social interactions, remains underexplored in Human-Robot Interaction (HRI). Inspired by the Turkish Ice Cream (TIC) vendor routine, we…