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Octo: An Open-Source Generalist Robot Policy The Octo model is a transformer-based diffusion policy, pretrained on 800k robot episodes from the Open X-Embodiment dataset It supports flexible task and observation definitions and can be quickly finetuned to new observation and action spaces
[2405. 12213] Octo: An Open-Source Generalist Robot Policy As a first step, we introduce Octo, a large transformer-based policy trained on 800k trajectories from the Open X-Embodiment dataset, the largest robot manipulation dataset to date
GitHub - octo-models octo: Octo is a transformer-based robot policy . . . Octo uses a modular attention structure in its transformer backbone, allowing it to be effectively finetuned to robot setups with new sensory inputs, action spaces, and morphologies, using only a small target domain dataset and accessible compute budgets
Octo：一个开源通才机器人策略 - 知乎 Octo 模型，开源通才机器人策略，可以通过微调适应新的机器人和任务（包括新的感官输入和动作空间）。 Octo 模型的设计强调灵活性和规模：它支持各种常用的机器人、传感器配置和动作，同时提供可在大量数据上进行训练的通用且可扩展的配方。
经典文献阅读之--Octo (开源的通用机器人模型) - CSDN博客 Octo模型的 设计强调灵活性和可扩展性，旨在支持各种常用的机器人、传感器配置和动作，同时提供一个通用且可扩展的训练方法，可以在大量数据上进行训练。 Octo 支持自然语言指令和目标图像、观察历史以及通过扩散解码实现的多模态动作分布。
| octo The Office of the Chief Technology Officer (OCTO) Connect DC program will host a Twitter
Octo: An Open-Source Generalist Robot Policy - arXiv. org Octo is the first GRP that can be effectively finetuned to new observations and action spaces and the first generalist robot manipulation policy that is fully open-source, including the training pipeline, model checkpoints, and data
Octo:AnOpen-SourceGeneralistRobotPolicy Octo Does Octo serve as a strong initialization for data-eficient finetuning to new tasks and robots, and does it improve over training from scratch and commonly used pretrained representations?