9 papers
Breaking Lock-In: Preserving Steerability under Low-Data VLA Post-Training
Suning Huang, Jiaqi Shao, Ke Wang +5
Have you ever post-trained a generalist vision-language-action (VLA) policy on a small demonstration dataset, only to find that it stops responding to new instructions and is limit…
Are Foundation Models the Route to Full-Stack Transfer in Robotics?
Freek Stulp, Samuel Bustamante, João Silvério +3
In humans and robots alike, transfer learning occurs at different levels of abstraction, from high-level linguistic transfer to low-level transfer of motor skills. In this article,…
SimToolReal: An Object-Centric Policy for Zero-Shot Dexterous Tool Manipulation
Kushal Kedia, Tyler Ga Wei Lum, Jeannette Bohg +1
The ability to manipulate tools significantly expands the set of tasks a robot can perform. Yet, tool manipulation represents a challenging class of dexterity, requiring grasping t…
Scaffolding Dexterous Manipulation with Vision-Language Models
Vincent de Bakker, Joey Hejna, Tyler Ga Wei Lum +6
Dexterous robotic hands are essential for performing complex manipulation tasks, yet remain difficult to train due to the challenges of demonstration collection and high-dimensiona…
CUPID: Curating Data your Robot Loves with Influence Functions
Christopher Agia, Rohan Sinha, Jingyun Yang +5
In robot imitation learning, policy performance is tightly coupled with the quality and composition of the demonstration data. Yet, developing a precise understanding of how indivi…
HoMeR: Learning In-the-Wild Mobile Manipulation via Hybrid Imitation and Whole-Body Control
Priya Sundaresan, Rhea Malhotra, Phillip Miao +7
We introduce HoMeR, an imitation learning framework for mobile manipulation that combines whole-body control with hybrid action modes that handle both long-range and fine-grained m…