4 papers
Learning Reactive Dexterous Grasping via Hierarchical Task-Space RL Planning and Joint-Space QP Control
Ho Jae Lee, Yonghyeon Lee, Alexander Alexiev +3
In this work, we propose a hybrid hierarchical control framework for reactive dexterous grasping that explicitly decouples high-level spatial intent from low-level joint execution.…
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…
High-Bandwidth Tactile-Reactive Control for Grasp Adjustment
Yonghyeon Lee, Tzu-Yuan Lin, Alexander Alexiev +1
Vision-only grasping systems are fundamentally constrained by calibration errors, sensor noise, and grasp pose prediction inaccuracies, leading to unavoidable contact uncertainty i…
Hierarchical Reactive Grasping via Task-Space Velocity Fields and Joint-Space Quadratic Programming
Yonghyeon Lee, Tzu-Yuan Lin, Alexander Alexiev +1
We present a fast and reactive grasping framework that combines task-space velocity fields with joint-space Quadratic Program (QP) in a hierarchical structure. Reactive, collision-…