[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-ea745180-90a1-4e71-a5ed-018b243359a7":3},{"id":4,"title":5,"summary":6,"original_url":7,"source_id":8,"tags":9,"published_at":23,"created_at":24,"modified_at":25,"is_published":26,"publish_type":27,"image_url":13,"view_count":28},"ea745180-90a1-4e71-a5ed-018b243359a7","Embodied.cpp 用 C++ 统一 runtime 终结 VLA 部署碎片化:HY-VLA 闭环 100%、WAM 显存砍到三分之一","【摘要】东南大学 SAIL Lab 推出 Embodied.cpp——一个面向异构机器人的 C++ 推理 runtime,采用五层模块化设计(input adapters \u002F sequence builders \u002F backbone execution \u002F head plugins \u002F deployment adapters),统一多速率闭环控制、batch-1 延迟优先推理和可扩展算子。在 HY-VLA、pi0.5 与 LingBot-VA Transformer block 上的实测表现硬核:VLA 闭环任务成功率 100% 与 91%,WAM Transformer block 显存从 312.2 MiB 砍到 88.1 MiB(不到三分之一)。GitHub 开源,可直接上车机器人与模拟器。\n\n【正文】过去两年,具身智能(VLA、WAM)在模型层不断刷出 SOTA,但「模型写得好,跑不起来」成了行业共同的尴尬——每个团队一套 Python 推理栈、对每种硬件写一份胶水代码、每个机器人一个独立 backend。东南大学 SAIL Lab 这次把视角从训练端转向部署端,推出 Embodied.cpp:一个面向异构机器人的 C++ 推理 runtime,直接登顶 Hugging Face 7 月 6 日 #2 trending。\n\n论文(arXiv 2607.02501)的核心思路是从 VLA\u002FWAM 模型架构里抽出\"共享执行路径\",分成五层:input adapters → sequence builders → backbone execution → head plugins → deployment adapters。这套抽象带来三件硬通货:统一支持多速率闭环控制、batch-1 延迟优先推理、可扩展算子与 I\u002FO,让同一份 runtime 跑在机器人、模拟器和不同加速器上,无需为每个模型家族重写一套胶水。\n\n实测数据也不含糊——HY-VLA 闭环任务成功率 100%、pi0.5 91%;WAM 基准把 Transformer block 的内存从 312.2 MiB 砍到 88.1 MiB,不到三分之一。代码开源在 github.com\u002FSEU-PAISys\u002FEmbodied.cpp,配套 Hugging Face 仓库同步发布,接口设计把模型侧的\"上肢动作\"和后端的\"硬件差异\"彻底解耦。\n\n在「模型月月新」的具身圈子里,真正把部署工程做扎实的项目反而稀缺——当各家还在比 demo 成功率,能稳定\"上车\"的运行时基础设施才是规模化落地的入场券。Embodied.cpp 提醒我们:具身智能的下半场,胜负不在参数大小,而在边缘设备能不能跑得稳、跑得快、跑得便宜。","https:\u002F\u002Farxiv.org\u002Fabs\u002F2607.02501","7437aeb9-930c-4866-a2e9-48003c1a792b",[10,14,17,20],{"id":11,"name":12,"slug":12,"description":13,"color":13},"40269b40-7942-4650-9672-ed2e6524d37a","ai-technology",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"0a93ec8e-ea39-4693-81de-563ca8c173f7","inference",{"id":18,"name":19,"slug":19,"description":13,"color":13},"499f4b56-819d-49a3-9609-33e775143b86","multimodal",{"id":21,"name":22,"slug":22,"description":13,"color":13},"b9bd9039-fcdb-41a8-b85b-fc1587def2b9","open-source","2026-07-06T18:05:00Z","2026-07-06T18:08:23.111756Z","2026-07-06T18:08:23.111765Z",true,"agent",4]