3.Vision-Language-Action Models 3.视觉语言动作模型 3.1. Pre-Trained Vision-Language Models 3.1. 预训练的视觉语言模型 3.2. Robot-Action Fine-tuning 3.2. 机器人动作微调 3.3. Real-Time Inference 3.3. 实时推理 4. Experiments 4. 实验 4.1. How does RT-2 perform on seen tasks and more important...
(一)introduction Vision-Language-Action models (VLAs),VLA模型能够将长时间任务分解为可执行的子任务。VLA这个概念是由RT-2提出,VLA是为解决具身AI的指令跟随任务而开发的。在语言条件下的机器人任务中,策略必须具备1)理解语言指令、2)视觉感知环境和3)生成适当动作的能力,这就需要虚拟学习器的多模态能力。 基于...
介绍RT-2模型基于Vision Language Model用互联网级图片文本对数据和机器人数据进行co-finetue生成Vision Language Action model用户robotic control应用,实验验证了其在泛化能力和新任务能力上明显由于RT-1模型。, 视频播放量 6、弹幕量 0、点赞数 1、投硬币枚数 0、收藏人
Large policies pretrained on a combination of Internet-scale vision-language data and diverse robot demonstrations have the potential to change how we teach robots new skills: rather than training new behaviors from scratch, we can fine-tune such vision-language-action (VLA) models to obtain ...
Consequently, we propose QUAdruped Robotic Transformer (QUART), a family of VLA models to integrate visual information and instructions from diverse modalities as input and generates executable actions for real-world robots and present QUAdruped Robot Dataset (QUARD), a large-scale multi-task dataset ...
Note: These installation instructions are for full-scale pretraining (and distributed fine-tuning); if looking to just run inference with OpenVLA models (or perform lightweight fine-tuning), see instructions above! This repository was built using Python 3.10, but should be backwards compatible with...
RT-2's architecture is based on well-established models, offering a high chance of success in diverse applications. With clear installation instructions and well-documented examples, you can integrate RT-2 into your systems quickly. RT-2 simplifies the complexities of multi-domaster understanding, ...
Existing semisupervised video action recognition methods trained from scratch rely heavily on augmentation techniques, complex architectures, and/or the use of other modalities while distillation-based methods use models that have only been trained for 2D computer vision tasks. In another...
Brohan, A., et al.: RT-2: vision-language-action models transfer web knowledge to robotic control. arXiv preprintarXiv:2307.15818(2023) Brohan, A., et al.: RT-1: robotics transformer for real-world control at scale (2023) Google Scholar ...
We study how vision-language models trained on Internet-scale data can be incorporated directly into end-to-end robotic control to boost generalization and enable emergent semantic reasoning. Our goal is to enable a single end-to-end trained model to both learn to map robot observations to acti...