Genie Envisioner：面向机器人操作的统一世界基础平台
Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation
AI总结：
本文提出Genie Envisioner平台，通过GE-Base视频扩散模型、GE-Act动作映射解码器、GE-Sim神经模拟器及EWMBench基准，实现机器人操作中策略学习、评估与仿真的统一，为通用具身智能提供可扩展基础。
摘要：
我们介绍了Genie Envisioner (GE)，这是一个用于机器人操作的统一世界基础平台，它在单一的视频生成框架内集成了策略学习、评估和仿真。其核心是GE-Base，这是一个大规模的、基于指令条件的视频扩散模型，在结构化潜在空间中捕捉真实世界机器人交互的空间、时间和语义动态。在此基础之上，GE-Act通过一个轻量级的流匹配解码器将潜在表示映射为可执行的动作轨迹，从而在最少监督下实现跨多种具身形态的精确且可泛化的策略推理。为了支持可扩展的评估和训练，GE-Sim作为一个基于动作条件的神经模拟器，为闭环策略开发生成高保真的rollout。该平台还配备了EWMBench，这是一个标准化基准套件，用于衡量视觉保真度、物理一致性以及指令-动作对齐。这些组件共同将Genie Envisioner确立为指令驱动、通用具身智能的可扩展且实用的基础。所有代码、模型和基准将公开发布。
英文摘要：
We introduce Genie Envisioner (GE), a unified world foundation platform for robotic manipulation that integrates policy learning, evaluation, and simulation within a single video-generative framework. At its core, GE-Base is a large-scale, instruction-conditioned video diffusion model that captures the spatial, temporal, and semantic dynamics of real-world robotic interactions in a structured latent space. Built upon this foundation, GE-Act maps latent representations to executable action trajectories through a lightweight, flow-matching decoder, enabling precise and generalizable policy inference across diverse embodiments with minimal supervision. To support scalable evaluation and training, GE-Sim serves as an action-conditioned neural simulator, producing high-fidelity rollouts for closed-loop policy development. The platform is further equipped with EWMBench, a standardized benchmark suite measuring visual fidelity, physical consistency, and instruction-action alignment. Together, these components establish Genie Envisioner as a scalable and practical foundation for instruction-driven, general-purpose embodied intelligence. All code, models, and benchmarks will be released publicly.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
