低成本机器人搭配统一视觉语言动作模型，实现在复杂场景下的可靠操作。
EveryDayVLA: A Vision-Language-Action Model for Affordable Robotic Manipulation
- 用统一模型同时输出离散与连续动作，实现端到端控制。
- 真实场景中性能比之前方法提升49%（分布内）和34.9%（分布外）。
- 整机成本低于300美元，适合家庭与实验室普及使用。
虽然视觉-语言-动作（VLA）模型可将视觉输入与语言指令直接映射为机器人动作，但通常依赖昂贵硬件，在新环境或杂乱场景中表现不佳。我们提出EverydayVLA，一种6自由度机械臂，组装成本低于300美元，具备一定承载能力和工作空间。采用单一统一模型联合输出离散与连续动作，其自适应时域集成机制通过监测运动不确定性，实现运行中动态重规划，确保安全可靠。在LIBERO数据集上，EverydayVLA达到顶尖成功率；真实世界测试中，其在分布内任务上优于先前方法49%，分布外任务上提升34.9%。结合先进VLA模型与低成本硬件，EverydayVLA推动了机器人基础模型的普及，为家庭与科研实验室提供经济可行方案。实验视频与详情见：https://everydayvla.github.io/
原文摘要 · Abstract (English)
While Vision-Language-Action (VLA) models map visual inputs and language instructions directly to robot actions, they often rely on costly hardware and struggle in novel or cluttered scenes. We introduce EverydayVLA, a 6-DOF manipulator that can be assembled for under $300, capable of modest payloads and workspace. A single unified model jointly outputs discrete and continuous actions, and our adaptive-horizon ensemble monitors motion uncertainty to trigger on-the-fly re-planning for safe, reliable operation. On LIBERO, EverydayVLA matches state-of-the-art success rates, and in real-world tests it outperforms prior methods by 49% in-distribution and 34.9% out-of-distribution. By combining a state-of-the-art VLA with cost-effective hardware, EverydayVLA democratizes access to a robotic foundation model and paves the way for economical use in homes and research labs alike. Experiment videos and details: https://everydayvla.github.io/
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