11 citations · 18 across the 9 of their papers we have counts for
9 papers
PointWorld: Scaling 3D World Models for In-The-Wild Robotic Manipulation
Wenlong Huang, Yu-Wei Chao, Arsalan Mousavian +4
Humans anticipate, from a glance and a contemplated action of their bodies, how the 3D world will respond, a capability that is equally vital for robotic manipulation. We introduce…
Slot-Level Robotic Placement via Visual Imitation from Single Human Video
Dandan Shan, Kaichun Mo, Wei Yang +4
The majority of modern robot learning methods focus on learning a set of pre-defined tasks with limited or no generalization to new tasks. Extending the robot skillset to novel tas…
Cosmos World Foundation Model Platform for Physical AI
NVIDIA, :, Niket Agarwal +76
Physical AI needs to be trained digitally first. It needs a digital twin of itself, the policy model, and a digital twin of the world, the world model. In this paper, we present th…
DiffusionSeeder: Seeding Motion Optimization with Diffusion for Rapid Motion Planning
Huang Huang, Balakumar Sundaralingam, Arsalan Mousavian +3
Running optimization across many parallel seeds leveraging GPU compute have relaxed the need for a good initialization, but this can fail if the problem is highly non-convex as all…
RVT-2: Learning Precise Manipulation from Few Demonstrations
Ankit Goyal, Valts Blukis, Jie Xu +3
In this work, we study how to build a robotic system that can solve multiple 3D manipulation tasks given language instructions. To be useful in industrial and household domains, su…
3D-MVP: 3D Multiview Pretraining for Robotic Manipulation
Shengyi Qian, Kaichun Mo, Valts Blukis +3
Recent works have shown that visual pretraining on egocentric datasets using masked autoencoders (MAE) can improve generalization for downstream robotics tasks. However, these appr…
Neural Implicit Representation for Building Digital Twins of Unknown Articulated Objects
Yijia Weng, Bowen Wen, Jonathan Tremblay +4
We address the problem of building digital twins of unknown articulated objects from two RGBD scans of the object at different articulation states. We decompose the problem into tw…
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…
M2T2: Multi-Task Masked Transformer for Object-centric Pick and Place
Wentao Yuan, Adithyavairavan Murali, Arsalan Mousavian +1
With the advent of large language models and large-scale robotic datasets, there has been tremendous progress in high-level decision-making for object manipulation. These generic m…