2 citations · 5 across the 4 of their papers we have counts for
6 papers
DemoStream: Batched Task-and-Motion-Plan Optimization for Automated Learning from Demonstration
Caelan Garrett, Neel Jawale, Fabio Ramos
Learning from demonstration is an effective strategy for endowing robots with manipulation capabilities but requires training on datasets comprised of massive amounts of demonstrat…
PEEK: Guiding and Minimal Image Representations for Zero-Shot Generalization of Robot Manipulation Policies
Jesse Zhang, Marius Memmel, Kevin Kim +6
Robotic manipulation policies often fail to generalize because they must simultaneously learn where to attend, what actions to take, and how to execute them. We argue that high-lev…
Cosmos-Transfer1: Conditional World Generation with Adaptive Multimodal Control
NVIDIA, :, Hassan Abu Alhaija +38
We introduce Cosmos-Transfer, a conditional world generation model that can generate world simulations based on multiple spatial control inputs of various modalities such as segmen…
HAMSTER: Hierarchical Action Models For Open-World Robot Manipulation
Yi Li, Yuquan Deng, Jesse Zhang +9
Large foundation models have shown strong open-world generalization to complex problems in vision and language, but similar levels of generalization have yet to be achieved in robo…
Aim My Robot: Precision Local Navigation to Any Object
Xiangyun Meng, Xuning Yang, Sanghun Jung +4
Existing navigation systems mostly consider "success" when the robot reaches within 1m radius to a goal. This precision is insufficient for emerging applications where the robot ne…
cuRobo: Parallelized Collision-Free Minimum-Jerk Robot Motion Generation
Balakumar Sundaralingam, Siva Kumar Sastry Hari, Adam Fishman +9
This paper explores the problem of collision-free motion generation for manipulators by formulating it as a global motion optimization problem. We develop a parallel optimization t…