7 papers · 1 filter
Flow with the Force Field: Learning 3D Compliant Flow Matching Policies from Force and Demonstration-Guided Simulation Data
Tianyu Li, Yihan Li, Zizhe Zhang +1
While visuomotor policy has made advancements in recent years, contact-rich tasks still remain a challenge. Robotic manipulation tasks that require continuous contact demand explic…
Elastic Motion Policy: An Adaptive Dynamical System for Robust and Efficient One-Shot Imitation Learning
Tianyu Li, Sunan Sun, Shubhodeep Shiv Aditya +1
Behavior cloning (BC) has become a staple imitation learning paradigm in robotics due to its ease of teaching robots complex skills directly from expert demonstrations. However, BC…
Out-of-Distribution Recovery with Object-Centric Keypoint Inverse Policy for Visuomotor Imitation Learning
George Jiayuan Gao, Tianyu Li, Nadia Figueroa
We propose an object-centric recovery (OCR) framework to address the challenges of out-of-distribution (OOD) scenarios in visuomotor policy learning. Previous behavior cloning (BC)…
SE(3) Linear Parameter Varying Dynamical Systems for Globally Asymptotically Stable End-Effector Control
Sunan Sun, Nadia Figueroa
Linear Parameter Varying Dynamical Systems (LPV-DS) encode trajectories into an autonomous first-order DS that enables reactive responses to perturbations, while ensuring globally…
Constraint-Aware Intent Estimation for Dynamic Human-Robot Object Co-Manipulation
Yifei Simon Shao, Tianyu Li, Shafagh Keyvanian +3
Constraint-aware estimation of human intent is essential for robots to physically collaborate and interact with humans. Further, to achieve fluid collaboration in dynamic tasks int…
Directionality-Aware Mixture Model Parallel Sampling for Efficient Linear Parameter Varying Dynamical System Learning
Sunan Sun, Haihui Gao, Tianyu Li +1
The Linear Parameter Varying Dynamical System (LPV-DS) is an effective approach that learns stable, time-invariant motion policies using statistical modeling and semi-definite opti…