{"id":60174,"date":"2026-01-15T04:41:26","date_gmt":"2026-01-14T20:41:26","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/60174.html"},"modified":"2026-01-15T04:41:26","modified_gmt":"2026-01-14T20:41:26","slug":"physbrain%ef%bc%9a%e4%bb%a5%e4%ba%ba%e7%b1%bb%e8%87%aa%e6%88%91%e4%b8%ad%e5%bf%83%e6%95%b0%e6%8d%ae%e4%b8%ba%e6%a1%a5%e6%a2%81%ef%bc%8c%e8%bf%9e%e6%8e%a5%e8%a7%86%e8%a7%89-%e8%af%ad%e8%a8%80%e6%a8%a1","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/60174.html","title":{"rendered":"PhysBrain\uff1a\u4ee5\u4eba\u7c7b\u81ea\u6211\u4e2d\u5fc3\u6570\u636e\u4e3a\u6865\u6881\uff0c\u8fde\u63a5\u89c6\u89c9-\u8bed\u8a00\u6a21\u578b\u548c\u7269\u7406\u667a\u80fd"},"content":{"rendered":"

25\u5e7412\u6708\u6765\u81ea\u9999\u6e2f\u79d1\u5927（\u5e7f\u5dde）\u3001\u4e2d\u5173\u6751\u5b66\u9662\u3001\u4e2d\u5173\u6751AI\u7814\u7a76\u6240\u3001\u5317\u4eac\u673a\u667a\u8d5b\u535a\u667a\u80fd\u79d1\u6280\u6709\u9650\u516c\u53f8（DeepCybo）\u3001\u54c8\u5de5\u5927\u548c\u534e\u4e2d\u79d1\u5927\u7684\u8bba\u6587\u201cPhysBrain: Human Egocentric Data as a Bridge from Vision Language Models to Physical Intelligence\u201d\u3002<\/p>\n

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\n

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\n\"\u8bf7\u6dfb\u52a0\u56fe\u7247\u63cf\u8ff0\"<\/p>\n

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\n

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\u6709\u4e86 PhysBrain，\u7814\u7a76\u8fd9\u4e9b\u81ea\u6211\u4e3a\u4e2d\u5fc3\u7684\u6539\u8fdb\u5982\u4f55\u5728VLA\u5b9e\u4f8b\u5316\u4e0b\u8fc1\u79fb\u5230\u4e0b\u6e38\u63a7\u5236\u3002\u76ee\u6807\u5e76\u975e\u63d0\u51fa\u65b0\u7684VLA\u67b6\u6784，\u800c\u662f\u5728\u5c3d\u91cf\u51cf\u5c11\u989d\u5916\u542f\u53d1\u5f0f\u65b9\u6cd5\u6216\u624b\u5de5\u8bbe\u8ba1\u5148\u9a8c\u4fe1\u606f\u5e26\u6765\u7684\u6df7\u6dc6\u56e0\u7d20\u540c\u65f6，\u8bc4\u4f30\u5176\u53ef\u8fc1\u79fb\u6027\u3002\u9075\u5faa\u4e24\u79cd\u88ab\u5e7f\u6cdb\u91c7\u7528\u7684\u793e\u533a\u8303\u5f0f：GR00T\u98ce\u683c\u548cPi\u98ce\u683c，\u5e76\u4fdd\u6301\u52a8\u4f5c\u4e13\u5bb6\u5728\u4e24\u79cd\u8303\u5f0f\u4e2d\u8f7b\u91cf\u7ea7\u4e14\u4e00\u81f4\u3002\u5efa\u5728PhysBrain\u4e4b\u4e0a\u7684VLA\u67b6\u6784\u5982\u56fe\u6240\u793a：
\n\"\u8bf7\u6dfb\u52a0\u56fe\u7247\u63cf\u8ff0\"<\/p>\n

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PhysGR00T（GR00T\u98ce\u683c\u7684VLA）\u3002\u5f15\u5165 PhysGR00T，\u5b83\u9075\u5faa GR00T N1.5（Bjorck，2025）\u4e2d\u7684\u53cc\u7cfb\u7edf\u8bbe\u8ba1：VLM \u4f5c\u4e3a\u7cfb\u7edf 2，\u7528\u4e8e\u751f\u6210\u9ad8\u5c42\u591a\u6a21\u6001\u8868\u793a；\u800c\u6d41\u5339\u914d（FM）\u52a8\u4f5c\u4e13\u5bb6（Liu，2022）\u4f5c\u4e3a\u7cfb\u7edf 1，\u7528\u4e8e\u751f\u6210\u8fde\u7eed\u52a8\u4f5c\u3002\u5177\u4f53\u800c\u8a00，PhysGR00T \u4f7f\u7528 VLM \u7684\u6700\u540e\u4e00\u5c42\u9690\u72b6\u6001 Z_t = HL<\/sup>_t \u4f5c\u4e3a\u6761\u4ef6\u4fe1\u53f7\u3002<\/p>\n

\u6d41\u5339\u914d（FM）\u4e13\u5bb6\u91c7\u7528\u6269\u6563transformer（DiT）（Peebles & Xie，2023）\u5b9e\u73b0，\u5b83\u901a\u8fc7\u4ea4\u53c9\u5173\u6ce8 Z_t \u6765\u5bf9\u52a8\u4f5c\u8f68\u8ff9\u8fdb\u884c\u53bb\u566a（VLM \u7279\u5f81\u662fK\/V\u5bf9，\u52a8\u4f5ctoken\u662f\u67e5\u8be2 Q）\u3002\u5728\u6574\u6d41\u53c2\u6570\u5316\u4e0b，\u5bf9\u9ad8\u65af\u566a\u58f0 \u03b5 \u223c N (0, 1) \u548c\u65f6\u95f4\u6807\u91cf \u03c4 \u2208 (0, 1] \u8fdb\u884c\u91c7\u6837，\u7136\u540e\u5728\u566a\u58f0\u548c\u76ee\u6807\u52a8\u4f5c\u5757\u4e4b\u95f4\u8fdb\u884c\u7ebf\u6027\u63d2\u503c，\u5f97\u5230\u5e26\u566a\u58f0\u7684\u8f68\u8ff9 a \u0303: a \u0303 = (1 \u2212 \u03c4 ) \u03b5 + \u03c4 a, v = a \u2212 \u03b5，\u8fd9\u91cc v \u662f\u76ee\u6807（\u4e0e\u65f6\u95f4\u65e0\u5173）\u901f\u5ea6，\u5b83\u5728\u8be5\u53c2\u6570\u5316\u4e0b\u5c06\u566a\u58f0\u8f68\u8ff9\u4f20\u9012\u5230\u6570\u636e\u8f68\u8ff9\u3002\u52a8\u4f5c\u4e13\u5bb6\u6a21\u578b\u57fa\u4e8e VLM \u7279\u5f81（\u4ee5\u53ca\u53ef\u9009\u7684\u672c\u4f53\u611f\u89c9\u72b6\u6001 s_t）\u9884\u6d4b\u8be5\u901f\u5ea6\u573a：v\u02c6 = f_\u03b8(a \u0303, \u03c4; Z_t, s_t)，\u5e76\u4f7f\u7528\u7b80\u5355\u7684\u56de\u5f52\u76ee\u6807 L_FM \u8fdb\u884c\u8bad\u7ec3\u3002<\/p>\n

\u5728\u63a8\u7406\u9636\u6bb5，\u4ece\u566a\u58f0\u5f00\u59cb，\u5e94\u7528\u5c11\u91cf FM \u53bb\u566a\u6b65\u9aa4（\u7528 steps = 8）\u6765\u83b7\u5f97\u52a8\u4f5c\u5757 a_t:t+K\u3002 K=16\u3002\u6b64\u8bbe\u8ba1\u63d0\u4f9b\u4e00\u4e2a\u53d7\u63a7\u73af\u5883，\u7528\u4e8e\u68c0\u9a8c\u81ea\u6211\u4e3a\u4e2d\u5fc3 VLM \u8868\u793a Z_t \u5bf9\u52a8\u4f5c\u9884\u6d4b\u7684\u4fe1\u606f\u91cf\u3002<\/p>\n

PhysPI（\u4e00\u79cd Pi \u98ce\u683c\u7684 VLA）\u3002\u8fd8\u5b9e\u4f8b\u5316\u4e00\u4e2a Pi \u98ce\u683c\u7684 VLA，\u79f0\u4e3a PhysPI，\u5176\u8bbe\u8ba1\u7406\u5ff5\u4e0e \u03c00（Black，2024）\u7c7b\u4f3c，\u5176\u4e2d VLM \u4e3b\u5e72\u4e0e\u52a8\u4f5c\u4e13\u5bb6\u66f4\u7d27\u5bc6\u5730\u8026\u5408\u3002\u4e0e\u4ec5\u4f7f\u7528\u6700\u540e\u4e00\u5c42 VLM（\u5982 PhysGR00T）\u4e0d\u540c，PhysPI \u4f7f\u7528\u591a\u4e2a VLM \u5c42\u6765\u7ea6\u675f DiT \u5757\u3002\u8bbe M \u4e3a\u52a8\u4f5c DiT \u4e2d Transformer \u5757\u7684\u6570\u91cf；\u53d6\u6700\u540e M \u4e2a VLM \u9690\u72b6\u6001 Z_t = HL\u2212M+1<\/sup>_t,\u2026,HL<\/sup>_t，\u5e76\u901a\u8fc7\u4ea4\u53c9\u6ce8\u610f\u673a\u5236，\u9010\u5c42\u5c06\u5b83\u4eec\u6ce8\u5165\u5230 DiT \u4e2d：u(i+1)<\/sup> = DiTBlock _i (Q = u(i)<\/sup>, KV = HL\u2212M+i<\/sup>_t), i = 1,\u2026,M，\u5176\u4e2du(0)<\/sup> \u662f\u5d4c\u5165\u7684（\u5e26\u566a\u58f0\u7684）\u52a8\u4f5c token\u5e8f\u5217\u3002FM \u8bad\u7ec3\u76ee\u6807\u4fdd\u6301\u4e0d\u53d8，\u4ecd\u4e3a L_FM\u3002<\/p>\n

PhysPI \u4e2d\u7684\u9010\u5c42\u6761\u4ef6\u5316\u589e\u5f3a\u4e2d\u95f4 VLM \u8868\u5f81\u4e0e\u52a8\u4f5c\u4e13\u5bb6\u4e4b\u95f4\u7684\u8026\u5408\u3002\u8fd9\u80fd\u591f\u6d4b\u8bd5\u5206\u5e03\u5728 VLM \u5c42\u4e0a\u81ea\u6211\u4e3a\u4e2d\u5fc3\u7684\u6539\u8fdb\u662f\u5426\u80fd\u66f4\u6709\u6548\u5730\u7528\u4e8e\u63a7\u5236\u3002<\/p>\n

\n

\u81ea\u6211\u4e2d\u5fc3\u7406\u89e3\u8bc4\u4f30<\/h3>\n

\u4e3a\u4e86\u5728\u516c\u5e73\u4e14\u65e0\u6cc4\u6f0f\u7684\u73af\u5883\u4e0b\u9a8c\u8bc1\u81ea\u6211\u4e2d\u5fc3\u7406\u89e3，\u7528 EgoThink（Cheng，2024）\u8fdb\u884c\u8bc4\u4f30\u3002EgoThink \u662f\u4e00\u4e2a\u5e7f\u6cdb\u4f7f\u7528\u7684\u81ea\u6211\u4e2d\u5fc3\u63a8\u7406\u57fa\u51c6\u6570\u636e\u96c6，\u57fa\u4e8e Ego4D \u6784\u5efa\u3002\u7531\u4e8e Ego4D \u5305\u542b\u5728 E2E \u6570\u636e\u96c6\u4e2d，\u56e0\u6b64\u5728\u51c6\u5907 PhysBrain \u4ee5\u8fdb\u884c EgoThink \u8bc4\u4f30\u65f6，\u8bad\u7ec3\u65b9\u6848\u6392\u9664 Ego4D \u90e8\u5206\u3002PhysBrain \u4ec5\u4f7f\u7528\u975e Ego4D \u5b50\u96c6\u8fdb\u884c\u8bad\u7ec3，\u5305\u62ec EgoDex（\u5b9e\u9a8c\u5ba4）\u548c BuildAI（\u5de5\u5382），\u5e76\u4e0e\u7b49\u89c4\u6a21\u7684\u901a\u7528\u6307\u4ee4\u6570\u636e\u6837\u672c\u6df7\u5408，\u4ee5\u4fdd\u7559\u5176\u901a\u7528\u7684\u89c6\u89c9\u8bed\u8a00\u80fd\u529b\u3002<\/p>\n

\u57fa\u7ebf\u3002\u4e3b\u8981\u5c06\u672c\u6587\u65b9\u6cd5\u4e0e\u4e24\u7c7b\u57fa\u7ebf\u6a21\u578b\u8fdb\u884c\u6bd4\u8f83：(i) VLM，\u5305\u62ec GPT-4 \u7b49\u95ed\u6e90\u6a21\u578b\u548c\u5e7f\u6cdb\u4f7f\u7528\u7684\u5f00\u6e90\u6a21\u578b（MiniGPT-4-7B\u3001LLaVA-1.5-7B\u3001LLaMA-3.2-11B \u548c Qwen2.5-VL-7B）；(ii) \u5177\u8eab\u8ba4\u77e5\u6a21\u578b，\u5305\u62ec VST-RL-7B (Yang，2025a) \u548c RoboBrain2.0-7B (Team，2025)，\u4ee5\u4fbf\u8fdb\u884c\u5168\u9762\u8bc4\u4f30\u3002<\/p>\n

\u8bc4\u4f30\u3002\u7528\u5df2\u53d1\u5e03\u7684\u6743\u91cd\u8fdb\u884c\u76f4\u63a5\u63a8\u7406\u6765\u8bc4\u4f30\u6bd4\u8f83\u65b9\u6cd5\u3002\u6240\u6709\u6a21\u578b\u7684\u8bc4\u4f30\u6761\u4ef6\u5747\u5df2\u6807\u51c6\u5316\u3002\u6240\u6709\u6a21\u578b\u5747\u4f7f\u7528\u76f8\u540c\u7684\u63d0\u793a\u6a21\u677f，\u5e76\u4e14\u6240\u6709 EgoThink \u5b50\u4efb\u52a1\u7684\u751f\u6210\u8f93\u51fa\u5747\u4f7f\u7528\u5355\u4e00\u7684 GPT-4o (Hurst，2024b) \u8bc4\u5224\u534f\u8bae\u8fdb\u884c\u8bc4\u5206\u3002\u8fd9\u4e9b\u63a7\u5236\u63aa\u65bd\u786e\u4fdd\u6027\u80fd\u5dee\u5f02\u53cd\u6620\u7684\u662f\u6a21\u578b\u80fd\u529b，\u800c\u975e\u6570\u636e\u6cc4\u9732\u3001\u63d0\u793a\u6027\u53d8\u5316\u6216\u8bc4\u5206\u4e0d\u4e00\u81f4\u3002<\/p>\n

\u57fa\u4e8e E2E \u6570\u636e\u96c6\u7684\u8865\u5145\u8bc4\u4f30<\/h3>\n

\u4e3a\u4e86\u8fdb\u4e00\u6b65\u9a8c\u8bc1\u6240\u63d0\u51fa\u7684 E2E \u6570\u636e\u96c6\u6709\u6548\u6027\u548c\u8865\u5145\u6027，\u4ec5\u4f7f\u7528 E2E \u6570\u636e\u5728\u89c6\u89c9\u7a7a\u95f4\u5fae\u8c03（VST）\u6a21\u578b\u8fdb\u884c\u76d1\u7763\u5fae\u8c03 (SFT)，\u800c\u4e0d\u5f15\u5165\u4efb\u4f55\u7a7a\u95f4\u80fd\u529b\u8bad\u7ec3 (SAT) \u7279\u6709\u7684\u8bad\u7ec3\u6837\u672c，\u4ece\u800c\u8bc4\u4f30SAT\u3002VST\u4f5c\u4e3a\u57fa\u7840\u6a21\u578b，\u56e0\u4e3a\u5b83\u5728\u5927\u89c4\u6a21\u3001\u9ad8\u8d28\u91cf\u7684\u7a7a\u95f4\u667a\u80fd\u6570\u636e\u96c6\u4e0a\u8fdb\u884c\u9884\u8bad\u7ec3，\u56e0\u6b64\u4e3a\u9759\u6001\u548c\u76ee\u6807\u4e3a\u4e2d\u5fc3\u7684\u7a7a\u95f4\u63a8\u7406\u63d0\u4f9b\u5f3a\u5927\u7684\u5148\u9a8c\u77e5\u8bc6\u3002\u8fd9\u79cd\u8bbe\u7f6e\u80fd\u591f\u8bc4\u4f30 E2E \u76d1\u7763\u662f\u5426\u80fd\u63d0\u4f9b\u8865\u5145\u4f18\u52bf，\u5c24\u5176\u662f\u5728\u81ea\u6211\u4e2d\u5fc3\u548c\u52a8\u6001\u7a7a\u95f4\u63a8\u7406\u65b9\u9762，\u8d85\u8d8a\u73b0\u6709\u7684\u7a7a\u95f4\u667a\u80fd\u8bad\u7ec3\u3002<\/p>\n

VLA\u4eff\u771f\u8bc4\u4f30<\/h3>\n

\u4e3a\u4e86\u9a8c\u8bc1\u6a21\u578b\u4f5c\u4e3a\u673a\u5668\u4eba\u63a7\u5236\u7684VLA\u90e8\u7f72\u6709\u6548\u6027，\u91c7\u7528PhysBrain\u4f5c\u4e3aVLM\u9aa8\u5e72\u7f51\u7edc，\u5e76\u4f7f\u7528\u4e0b\u6e38\u673a\u5668\u4eba\u6570\u636e\u5728VLA\u8303\u5f0f\u4e2d\u5bf9\u5176\u8fdb\u884c\u5fae\u8c03\u3002\u7136\u540e，\u7528WidowX\u673a\u5668\u4eba，\u5728SimplerEnv（Li，2024c）\u4eff\u771f\u57fa\u51c6\u4e0a\u8fdb\u884c\u8bc4\u4f30\u3002<\/p>\n

\u5b9e\u9a8c\u8bbe\u7f6e<\/h4>\n

\u67b6\u6784\u3002\u7528PhysGR00T \u548c PhysPI \u67b6\u6784\u5b9e\u4f8b\u5316 VLA \u6a21\u578b\u3002VLM \u7ec4\u4ef6\u4f7f\u7528 PhysBrain \u7684\u6743\u91cd\u8fdb\u884c\u521d\u59cb\u5316，\u800c\u52a8\u4f5c\u4e13\u5bb6\u7ec4\u4ef6\u5219\u4f7f\u7528\u968f\u673a\u6743\u91cd\u8fdb\u884c\u521d\u59cb\u5316\u3002<\/p>\n

\u8bad\u7ec3\u3002\u4e3a\u4e86\u4f7f VLM \u9002\u5e94 VLA \u67b6\u6784\u548c\u76ee\u6807\u673a\u5668\u4eba\u5e73\u53f0，\u9075\u5faa starVLA (starVLA Community, 2025) \u6846\u67b6\u7684\u8bad\u7ec3\u914d\u7f6e，\u5e76\u5728 Open X-Embodiment (OXE) (O\u2019Neill et al., 2024) \u6570\u636e\u96c6\u7684\u4e24\u4e2a\u5b50\u96c6\u4e0a\u5bf9 VLA \u8fdb\u884c\u5fae\u8c03：Bridge (Walke et al., 2023) \u548c Fractal (Brohan et al., 2023)\u3002\u6bcf\u6b21\u8bad\u7ec3\u8fd0\u884c\u5927\u7ea6\u9700\u8981 22 \u5c0f\u65f6，\u4f7f\u7528 8 \u4e2a NVIDIA H100 GPU\u3002<\/p>\n

\u8bc4\u4f30\u3002\u8be5\u57fa\u51c6\u6d4b\u8bd5\u5305\u542b\u56db\u4e2a\u64cd\u4f5c\u4efb\u52a1：\u201c\u5c06\u52fa\u5b50\u653e\u5728\u6bdb\u5dfe\u4e0a\u201d\u3001\u201c\u5c06\u80e1\u841d\u535c\u653e\u5728\u76d8\u5b50\u4e0a\u201d\u3001\u201c\u5c06\u7eff\u8272\u79ef\u6728\u5806\u653e\u5728\u9ec4\u8272\u79ef\u6728\u4e0a\u201d\u3001\u201c\u5c06\u8304\u5b50\u653e\u5165\u9ec4\u8272\u7bee\u5b50\u4e2d\u201d\u3002\u5bf9\u4e8e\u6bcf\u4e2a\u4efb\u52a1，\u7528 SimplerEnv \u4ee3\u7801\u5e93\u63d0\u4f9b\u7684\u5b98\u65b9\u8bc4\u4f30\u811a\u672c（Li ，2024c）\u6765\u8bc4\u4f30 VLA \u7b56\u7565\u3002\u4e3a\u4e86\u964d\u4f4e\u968f\u673a\u6027，\u8fd0\u884c\u4e94\u6b21\u72ec\u7acb\u7684\u8bd5\u9a8c，\u5e76\u62a5\u544a\u5e73\u5747\u6027\u80fd\u3002<\/p>\n

\u57fa\u7ebf\u3002\u4e3b\u8981\u5c06\u65b9\u6cd5\u4e0e\u4e24\u7c7b\u57fa\u7ebf\u8fdb\u884c\u6bd4\u8f83：（i）VLA \u57fa\u7ebf，\u5176\u4e2d\u5305\u62ec\u51e0\u4e2a\u5e7f\u6cdb\u4f7f\u7528\u7684 VLA \u6a21\u578b（RT-1-X\u3001Octo\u3001OpenVLA\u3001RoboVLM\u3001TraceVLA\u3001SpatialVLA\u3001CogACT\u3001VideoVLA \u548c \u03c00）；\u4ee5\u53ca（ii）VLM \u57fa\u7ebf，\u5176\u4e2d\u5728 VLA \u8303\u5f0f\u4e0b\u5fae\u8c03\u51e0\u4e2a\u5e38\u7528\u7684 VLM \u6a21\u578b（RoboBrain2.0\u3001VST-RL \u548c Spatial-SSRL），\u5e76\u4f7f\u7528\u4e0e\u65b9\u6cd5\u76f8\u540c\u7684\u8bad\u7ec3\u914d\u7f6e\u5bf9\u5176\u8fdb\u884c\u8bc4\u4f30\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

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