vla

Dexbotic: Open-Source Vision-Language-Action Toolbox

🐕 MindPaw — 基于 ESP8266 的开源桌面四足机器狗，支持语音、手势、网页遥控、豆包 AI 对话与 PAD 情感交互。可选 AI Infra 网关，适合机器人入门、嵌入式 AI、边缘 Agent 与 HRI 研究。

An Open-World Foundation Model for General-Purpose Embodied Intelligence.

NVIDIA Alpamayo 1 Nano is an open 10B reasoning VLA model for autonomous vehicles that pairs driving trajectories with Chain-of-Causation reasoning.

[ICLR 2026] SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning

A Pragmatic VLA Foundation Model

[RSS 2025] Learning to Act Anywhere with Task-centric Latent Actions

InternRobotics' open platform for building generalized navigation foundation models.

Unified Codebase for Advanced World Models.

[NeurIPS 2025 spotlight] Official implementation for "FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving"

🚀🚀🚀A collection of some awesome public projects about Large Language Model(LLM), Vision Language Model(VLM), Vision Language Action(VLA), AI Generated Content(AIGC), the related Datasets and Applications.

🔥 SpatialVLA: a spatial-enhanced vision-language-action model that is trained on 1.1 Million real robot episodes. Accepted at RSS 2025.

本项目旨在为致力于进入VLA(Vision-Language-Action)领域的算法工程师提供一份全中文、实战导向的学习/面试手册。 不同于通用的 CV/NLP 面试指南，本项目聚焦于 Robotics 特有的挑战

A high-performance framework for training LLMs, VLMs, diffusion, and embodied models on NVIDIA GPUs and Kunlun XPUs. Supports Pi0.5, GR00T-N1.7, FastWAM, Cosmos3, DreamZero, DeepSeek-V4, GLM-5.3, Kimi-K3 and more.

Open source evals for physical AI. Run any LLM/VLA on any arm/humanoid against any real/sim benchmark.

Running VLA at 30Hz frame rate and 480Hz trajectory frequency

人形机器人运动智能论文、开源项目、产业与求职知识库

FlashRT is a high-performance realtime inference engine for small-batch, latency-sensitive AI workloads. The flagship integration is production VLA control for Pi0, Pi0.5, GROOT N1.6, and Pi0-FAST. Also support llm e.g, qwen3.6-27B

[ICLR2026] Official implementation for "JanusVLN: Decoupling Semantics and Spatiality with Dual Implicit Memory for Vision-Language Navigation"

DeepThinkVLA: Enhancing Reasoning Capability of Vision-Language-Action Models