1 citations · 4 across the 5 of their papers we have counts for
5 papers
Flexible Multitask Learning with Factorized Diffusion Policy
Chaoqi Liu, Haonan Chen, Sigmund H. Høeg +4
Multitask learning poses significant challenges due to the highly multimodal and diverse nature of robot action distributions. However, effectively fitting policies to these comple…
Particle-Grid Neural Dynamics for Learning Deformable Object Models from RGB-D Videos
Kaifeng Zhang, Baoyu Li, Kris Hauser +1
Modeling the dynamics of deformable objects is challenging due to their diverse physical properties and the difficulty of estimating states from limited visual information. We addr…
Localized Graph-Based Neural Dynamics Models for Terrain Manipulation
Chaoqi Liu, Yunzhu Li, Kris Hauser
Predictive models can be particularly helpful for robots to effectively manipulate terrains in construction sites and extraterrestrial surfaces. However, terrain state representati…
AdaptiGraph: Material-Adaptive Graph-Based Neural Dynamics for Robotic Manipulation
Kaifeng Zhang, Baoyu Li, Kris Hauser +1
Predictive models are a crucial component of many robotic systems. Yet, constructing accurate predictive models for a variety of deformable objects, especially those with unknown p…
Efficient Automatic Tuning for Data-driven Model Predictive Control via Meta-Learning
Baoyu Li, William Edwards, Kris Hauser
AutoMPC is a Python package that automates and optimizes data-driven model predictive control. However, it can be computationally expensive and unstable when exploring large search…