openpi holds open-source models and packages for robotics, published by the Physical Intelligence team. Currently, this repo contains two types of models: the π₀-FAST model, an autoregressive VLA, based on the FAST action tokenizer.

Oct 31, 2024 · In this paper, we discuss how generalist robot policies (i.e., robot foundation models) can address these challenges, and how we can design effective generalist robot policies for complex and highly dexterous tasks.

embodiment dataset with a variety of dexterous manipulation tasks. The model is adapted to robot control by adding a separate action expert that produces continuous actions .

Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.

This repo implements the pi0 model from Physical Intelligence (Pi) based on my knowledge of the paper.

Feb 4, 2025 · π0 (Pi-Zero) is a Vision-Language-Action (VLA) model, developed by the Physical Intelligence team designed for generalist robot control. It builds upon large-scale pretraining and flow matching-based action generation, enabling robots to perform dexterous manipulation tasks across different embodiments.

Oct 31, 2024 · In this paper, we discuss how generalist robot policies (i.e., robot foundation models) can address these challenges, and how we can design effective generalist robot policies for complex and highly dexterous tasks.

Implementation of π₀ the robotic foundation model architecture proposed by Physical Intelligence.

24年10月底，来自Physical Intelligence公司的研究者们提出了一个原型模型和学习框架，称之为π0. 其中的 Kevin Black 是伯克利AI的博士生，也是该公司的研究员. 下图图1中展示了该模型和系统： 先在高度多样化的机器人数据上进行预训练——变成了相比不二次预训练情况下更强大的VLA (类似7-RT-2、24-OpenVLA、55-Tinyvla)，然后针对具体任务进行微调. 而想达到这个目标， …

Oct 31, 2024 · Our first step is π0, a prototype model that combines large-scale multi-task and multi-robot data collection with a new network architecture to enable the most capable and dexterous generalist robot policy to date.