44 citations · 94 across the 22 of their papers we have counts for
13 papers · 1 filter
RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
Jenai Xuning Yang, Rishit Dagli, Alex Zook +5
The pursuit of general-purpose robotics has yielded impressive foundation models, yet simulation-based benchmarking remains a bottleneck due to rapid performance saturation and a l…
VLA-0: Building State-of-the-Art VLAs with Zero Modification
Ankit Goyal, Hugo Hadfield, Xuning Yang +2
Vision-Language-Action models (VLAs) hold immense promise for enabling generalist robot manipulation. However, the best way to build them remains an open question. Current approach…
ManiFlow: A General Robot Manipulation Policy via Consistency Flow Training
Ge Yan, Jiyue Zhu, Yuquan Deng +8
This paper introduces ManiFlow, a visuomotor imitation learning policy for general robot manipulation that generates precise, high-dimensional actions conditioned on diverse visual…
OG-VLA: Orthographic Image Generation for 3D-Aware Vision-Language Action Model
Ishika Singh, Ankit Goyal, Stan Birchfield +3
We introduce OG-VLA, a novel architecture and learning framework that combines the generalization strengths of Vision Language Action models (VLAs) with the robustness of 3D-aware…
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…
Discovering Robotic Interaction Modes with Discrete Representation Learning
Liquan Wang, Ankit Goyal, Haoping Xu +1
Human actions manipulating articulated objects, such as opening and closing a drawer, can be categorized into multiple modalities we define as interaction modes. Traditional robot…
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…
AdaDemo: Data-Efficient Demonstration Expansion for Generalist Robotic Agent
Tongzhou Mu, Yijie Guo, Jie Xu +4
Encouraged by the remarkable achievements of language and vision foundation models, developing generalist robotic agents through imitation learning, using large demonstration datas…
Shelving, Stacking, Hanging: Relational Pose Diffusion for Multi-modal Rearrangement
Anthony Simeonov, Ankit Goyal, Lucas Manuelli +5
We propose a system for rearranging objects in a scene to achieve a desired object-scene placing relationship, such as a book inserted in an open slot of a bookshelf. The pipeline…
RVT: Robotic View Transformer for 3D Object Manipulation
Ankit Goyal, Jie Xu, Yijie Guo +3
For 3D object manipulation, methods that build an explicit 3D representation perform better than those relying only on camera images. But using explicit 3D representations like vox…
ProgPrompt: Generating Situated Robot Task Plans using Large Language Models
Ishika Singh, Valts Blukis, Arsalan Mousavian +6
Task planning can require defining myriad domain knowledge about the world in which a robot needs to act. To ameliorate that effort, large language models (LLMs) can be used to sco…
IFOR: Iterative Flow Minimization for Robotic Object Rearrangement
Ankit Goyal, Arsalan Mousavian, Chris Paxton +4
Accurate object rearrangement from vision is a crucial problem for a wide variety of real-world robotics applications in unstructured environments. We propose IFOR, Iterative Flow…