{ "table_of_contents": [ { "title": "Humanoid robots 2026", "heading_level": null, "page_id": 1, "polygon": [ [ 32.89794921875, 98.7734375 ], [ 182.75942993164062, 98.7734375 ], [ 182.75942993164062, 114.22216796875 ], [ 32.89794921875, 114.22216796875 ] ] }, { "title": "Contents", "heading_level": null, "page_id": 2, "polygon": [ [ 33.57699966430664, 41.859375 ], [ 180.58900451660156, 40.390625 ], [ 180.58900451660156, 72.81536865234375 ], [ 33.57699966430664, 72.81536865234375 ] ] }, { "title": "1/ A trillion-dollar market \u2013 with uncertain timing", "heading_level": null, "page_id": 3, "polygon": [ [ 32.89794921875, 40.390625 ], [ 404.3110656738281, 40.390625 ], [ 404.3110656738281, 58.076904296875 ], [ 32.89794921875, 58.076904296875 ] ] }, { "title": "A Not all humanoids are created equal", "heading_level": null, "page_id": 4, "polygon": [ [ 31.845214843749996, 403.7684630738523 ], [ 215.1502086230876, 403.171875 ], [ 215.1502086230876, 412.7744510978044 ], [ 31.845214843749996, 413.453125 ] ] }, { "title": "THE EMERGING HUMANOID ROBOTICS \nINDUSTRY ECOSYSTEM", "heading_level": null, "page_id": 5, "polygon": [ [ 32.89794921875, 207.828125 ], [ 213.4405975341797, 207.828125 ], [ 213.4405975341797, 232.12054443359375 ], [ 32.89794921875, 232.12054443359375 ] ] }, { "title": "B The next automotive industry?", "heading_level": null, "page_id": 5, "polygon": [ [ 33.95068359375, 351.3984375 ], [ 186.6157989501953, 349.9296875 ], [ 186.6157989501953, 362.1245422363281 ], [ 33.95068359375, 362.1245422363281 ] ] }, { "title": "2/ Technological readiness", "heading_level": null, "page_id": 7, "polygon": [ [ 32.235048678720446, 40.526946107784426 ], [ 241.38803894297635, 40.526946107784426 ], [ 241.38803894297635, 57.0379241516966 ], [ 32.235048678720446, 57.0379241516966 ] ] }, { "title": "D Mind the gap", "heading_level": null, "page_id": 7, "polygon": [ [ 32.984700973574405, 311.375 ], [ 106.45062586926285, 309.90625 ], [ 106.45062586926285, 321.96407185628743 ], [ 32.984700973574405, 321.96407185628743 ] ] }, { "title": "Mass commercialization in 1-3 years", "heading_level": null, "page_id": 8, "polygon": [ [ 225.54833984374997, 344.7890625 ], [ 386.36578369140625, 343.3203125 ], [ 386.36578369140625, 355.3959655761719 ], [ 225.54833984374997, 355.3959655761719 ] ] }, { "title": "The cost-performance imperative:", "heading_level": null, "page_id": 9, "polygon": [ [ 60.26904296874999, 313.2109375 ], [ 214.32101440429688, 311.7421875 ], [ 214.32101440429688, 323.00836181640625 ], [ 59.21630859374999, 323.00836181640625 ] ] }, { "title": "The durability gap:", "heading_level": null, "page_id": 9, "polygon": [ [ 58.42675781249999, 405.50836181640625 ], [ 144.5708465576172, 404.640625 ], [ 144.5708465576172, 414.00836181640625 ], [ 58.42675781249999, 414.921875 ] ] }, { "title": "Ongoing technology transitions:", "heading_level": null, "page_id": 9, "polygon": [ [ 60.00585937499999, 509.50836181640625 ], [ 204.35305786132812, 508.18749999999994 ], [ 204.35305786132812, 518.0083618164062 ], [ 60.00585937499999, 518.46875 ] ] }, { "title": "Actuators \u2013 the core value driver", "heading_level": null, "page_id": 9, "polygon": [ [ 287.13330078125, 208.9296875 ], [ 431.8603515625, 207.4609375 ], [ 431.8603515625, 219.00823974609375 ], [ 286.08056640625, 219.00823974609375 ] ] }, { "title": "Software and ecosystem maturity", "heading_level": null, "page_id": 9, "polygon": [ [ 276.07958984375, 456.78125 ], [ 427.17950439453125, 455.3125 ], [ 427.17950439453125, 466.0082702636719 ], [ 276.07958984375, 466.0082702636719 ] ] }, { "title": "Software and ecosystem maturity assessment", "heading_level": null, "page_id": 10, "polygon": [ [ 48.16259765625, 70.1328125 ], [ 313.2611389160156, 68.6640625 ], [ 313.2611389160156, 83.90228271484375 ], [ 47.10986328125, 83.90228271484375 ] ] }, { "title": "VLM1\nTraining \ndata\nSupply \nchain\nRegulation\nDescription Current status Key challenges\nSoftware \u2013 trailing hardware by 3-5 years \nEcosystem \u2013 not yet ready for mass commercialization \n\u2022 Core system \ncombining perception \nand reasoning\n\u2022 Enables zero-shot \nlearning2\n\u2022 Multimodal datasets: \nvision, tactile, \nproprioception, force \nfeedback\n\u2022 Capture diverse \nenvironments, \ntasks, failure modes, \nrecovery strategies\n\u2022 Global supplier \nnetworks across US, \nEurope and China with \nregional specialization\n\u2022 Integration of existing \nautomotive, electronics \nand robotics supply \nchains\n\u2022 Safety standards for \nhuman-humanoid \nrobot collaboration \n\u2022 Export controls \n(ICTS), AI governance \n(EU AI Act), product \ncompliance (CE, FCC) \n\u2022 GenAI compressing \ndevelopment cycle \n\u2022 Controlled environment \ntasks approaching human \nlevel\n\u2022 Open-ended environments \nstill need 5-10 years\n\u2022 Public data scarcity: LLM \ntext corpora exist; robot \nmanipulation data doesn't \nexist at scale\n\u2022 Limited open-source \ndatasets for robotics \nAI training\n\u2022 Leading humanoid OEMs are \ncollecting proprietary data\n\u2022 No mature end-to-end \nsupply chain yet: US focused \non software; China focused \non industrialization\n\u2022 Dual supply chain \u2013 \nregulated components \n(high-cost) sourced from \nWestern countries; standard \ncomponents (low-cost) \nsourced from China\n\u2022 No harmonized global \nstandards: US/EU/China \npursuing divergent \nregulatory paths\n\u2022 ICTS impact: 13 critical \ncomponents face exclusion \nfrom Chinese suppliers \n\u2022 Safety certification \nundefined: existing \nstandards do not apply \nto humanoids\n\u2022 Difficulty with context-\nbased reasoning\n\u2022 Reliable transfer of \nvirtual training to \nphysical environment\n\u2022 Local computing power \nrequirement is high \n(200+ TOPS)\n\u2022 Data generation bottleneck \nprevents LLM-alike \nlarge-scale training\n\u2022 Need labeled, multi-angle \nand multimodal recordings \n\u2013 exponentially more \nexpensive than text \n\u2022 Data becomes a \ncompetitive advantage \nand proprietary asset of \nleading OEMs, leading to a \nfragmented ecosystem\n\u2022 Most Tier 2 suppliers are still \nin the testing phases: 1-2 \nyears minimum to progress \nto mass production stage\n\u2022 Suppliers are hesitant to \ninvest in capacity \n\u2022 ICTS/export controls force \n2-3x cost premiums for \ncritical components \n\u2022 Standards timeline: 2-3 \nyears minimum for ISO \nratification, industry \nadoption, certification \ninfrastructure\n\u2022 Fragmented regulation \nacross US, EU and China \n\u2022 Unclear who bears \nresponsibility for AI-driven \nphysical errors", "heading_level": null, "page_id": 10, "polygon": [ [ 32.89794921875, 111.2218017578125 ], [ 502.5633850097656, 109.7890625 ], [ 502.5633850097656, 620.1796875 ], [ 31.845214843749996, 621.6484375 ] ] }, { "title": "Data as the core constraint", "heading_level": null, "page_id": 11, "polygon": [ [ 34.47705078125, 493.8671875 ], [ 155.01513671875, 493.8671875 ], [ 154.9506378173828, 505.0082550048828 ], [ 33.42431640625, 505.0082550048828 ] ] }, { "title": "Simulation as an accelerator, not a substitute", "heading_level": null, "page_id": 11, "polygon": [ [ 34.59770202636719, 612.1015625 ], [ 234.06716918945312, 612.1015625 ], [ 234.06716918945312, 622.0082550048828 ], [ 33.95068359375, 622.0082550048828 ] ] }, { "title": "Compute infrastructure as a barrier to entry", "heading_level": null, "page_id": 11, "polygon": [ [ 276.07958984375, 207.4609375 ], [ 470.8747863769531, 205.9921875 ], [ 470.8747863769531, 219.00823974609375 ], [ 275.02685546875, 219.00823974609375 ] ] }, { "title": "3/ Two ecosystems, two scaling curves", "heading_level": null, "page_id": 13, "polygon": [ [ 31.48539638386648, 41.125 ], [ 332.84561891515995, 41.125 ], [ 332.84561891515995, 55.8125 ], [ 31.48539638386648, 55.8125 ] ] }, { "title": "China's deployment-led strategy and the West's Al-driven approach", "heading_level": null, "page_id": 13, "polygon": [ [ 31.48539638386648, 66.09375 ], [ 404.0625869262865, 66.09375 ], [ 404.0625869262865, 99.875 ], [ 31.48539638386648, 99.875 ] ] }, { "title": "WESTERN ECOSYSTEM: AI-FIRST, CAPITAL-RICH, SCALE-POOR", "heading_level": null, "page_id": 13, "polygon": [ [ 32.634765625, 350.6640625 ], [ 261.62865090403335, 350.6640625 ], [ 261.62865090403335, 371.9609375 ], [ 32.634765625, 371.9609375 ] ] }, { "title": "CHINESE ECOSYSTEM: DEPLOYMENT-FIRST, SCALE-DRIVEN LEARNING", "heading_level": null, "page_id": 13, "polygon": [ [ 32.984700973574405, 559.59375 ], [ 239.13908205841446, 559.59375 ], [ 239.13908205841446, 580.8862275449102 ], [ 32.984700973574405, 580.8862275449102 ] ] }, { "title": "STRATEGIC IMPLICATIONS", "heading_level": null, "page_id": 13, "polygon": [ [ 274.763671875, 260.3359375 ], [ 401.06397774687065, 258.8671875 ], [ 401.06397774687065, 268.67864271457086 ], [ 273.7109375, 268.67864271457086 ] ] }, { "title": "F Different regions, different strengths", "heading_level": null, "page_id": 14, "polygon": [ [ 34.63999938964844, 220.6796875 ], [ 216.86328124999997, 220.6796875 ], [ 216.86328124999997, 232.12451171875 ], [ 34.63999938964844, 232.12451171875 ] ] }, { "title": "4/ Where value will emerge first", "heading_level": null, "page_id": 15, "polygon": [ [ 32.235048678720446, 40.526946107784426 ], [ 278.87065368567454, 40.526946107784426 ], [ 278.87065368567454, 56.1796875 ], [ 32.235048678720446, 56.1796875 ] ] }, { "title": "G The labor pool is shrinking", "heading_level": null, "page_id": 15, "polygon": [ [ 32.984700973574405, 351.03125 ], [ 166.42280945757997, 349.5625 ], [ 166.42280945757997, 360.2395209580838 ], [ 32.984700973574405, 361.3125 ] ] }, { "title": "Working-age population in 2025 & corresponding unemployment rate", "heading_level": null, "page_id": 15, "polygon": [ [ 32.984700973574405, 383.5049900199601 ], [ 339.5924895688456, 382.609375 ], [ 339.5924895688456, 393.2614770459082 ], [ 32.984700973574405, 393.2614770459082 ] ] }, { "title": "Global labor development", "heading_level": null, "page_id": 15, "polygon": [ [ 32.984700973574405, 613.9081836327344 ], [ 149.18080667593878, 613.9081836327344 ], [ 149.18080667593878, 623.6646706586826 ], [ 32.984700973574405, 623.6646706586826 ] ] }, { "title": "Working-age population forecast for 2050 & working-age population growth compared to 2025", "heading_level": null, "page_id": 16, "polygon": [ [ 32.984700973574405, 382.754491017964 ], [ 455.78859527121, 382.754491017964 ], [ 455.78859527121, 393.2614770459082 ], [ 32.634765625, 393.9921875 ] ] }, { "title": "H When workers disappear, machines take the night shift", "heading_level": null, "page_id": 17, "polygon": [ [ 34.2138671875, 351.03125 ], [ 300.79156494140625, 349.5625 ], [ 300.79156494140625, 362.1245422363281 ], [ 33.1611328125, 362.1245422363281 ] ] }, { "title": "Change in working-age population (aged 15-64), \n2025-50 [%]", "heading_level": null, "page_id": 17, "polygon": [ [ 33.6875, 381.140625 ], [ 249.561279296875, 379.671875 ], [ 249.561279296875, 401.33917236328125 ], [ 33.6875, 401.33917236328125 ] ] }, { "title": "For German companies", "heading_level": null, "page_id": 17, "polygon": [ [ 42.37255859375, 493.5 ], [ 146.0465545654297, 492.03125 ], [ 146.0465545654297, 502.9617462158203 ], [ 42.37255859375, 502.9617462158203 ] ] }, { "title": "4 months", "heading_level": null, "page_id": 17, "polygon": [ [ 157.64697265625, 505.24999999999994 ], [ 237.12841796874997, 503.78125 ], [ 237.12841796874997, 526.8042144775391 ], [ 157.64697265625, 526.8042144775391 ] ] }, { "title": "For manufacturing specifically", "heading_level": null, "page_id": 17, "polygon": [ [ 43.42529296875, 593.375 ], [ 178.07540893554688, 591.90625 ], [ 178.07540893554688, 602.8367462158203 ], [ 42.37255859375, 602.8367462158203 ] ] }, { "title": "Key levers for tackling labor scarcity", "heading_level": null, "page_id": 17, "polygon": [ [ 276.869140625, 381.140625 ], [ 437.0465393066406, 379.671875 ], [ 437.0465393066406, 391.421875 ], [ 276.869140625, 392.890625 ] ] }, { "title": "Talent management\nTalent acquisition\nProcess maturity & repeatability", "heading_level": null, "page_id": 17, "polygon": [ [ 319.0575866699219, 555.1875 ], [ 492.67968749999994, 553.71875 ], [ 491.62695312499994, 609.894287109375 ], [ 319.0575866699219, 609.894287109375 ] ] }, { "title": "Organization & talent\nOutsourcing potential\nValue and supply chain setup\nEtc.", "heading_level": null, "page_id": 17, "polygon": [ [ 295.55517578125, 619.4453125 ], [ 497.15380859374994, 617.9765625 ], [ 496.10107421874994, 683.1615829467773 ], [ 294.50244140625, 683.1615829467773 ] ] }, { "title": "I Where automation still struggles", "heading_level": null, "page_id": 18, "polygon": [ [ 33.95068359375, 325.6953125 ], [ 193.3765869140625, 324.2265625 ], [ 193.3765869140625, 336.1245422363281 ], [ 33.95068359375, 336.1245422363281 ] ] }, { "title": "SIMPLE USE CASES \u2013 LEARNING THE \nTECHNOLOGY", "heading_level": null, "page_id": 19, "polygon": [ [ 33.523197174072266, 298.890625 ], [ 203.10032653808594, 298.890625 ], [ 203.10032653808594, 323.1175537109375 ], [ 32.89794921875, 323.1175537109375 ] ] }, { "title": "MEDIUM-COMPLEXITY USE CASES \u2013 UNLOCKING \nFIRST ADDITIONAL VALUE", "heading_level": null, "page_id": 19, "polygon": [ [ 34.2138671875, 599.6171875 ], [ 262.05401611328125, 599.6171875 ], [ 262.05401611328125, 622.1175231933594 ], [ 34.2138671875, 622.1175231933594 ] ] }, { "title": "HIGH-COMPLEXITY USE CASES \u2013 EXPANDING \nINDUSTRIAL AUTOMATION", "heading_level": null, "page_id": 19, "polygon": [ [ 276.60595703125, 482.8515625 ], [ 488.36376953125, 481.3828125 ], [ 488.36376953125, 505.1215362548828 ], [ 275.55322265625, 505.1215362548828 ] ] }, { "title": "5/ Strategic implications for industry players", "heading_level": null, "page_id": 20, "polygon": [ [ 274.37273991655076, 40.7578125 ], [ 467.7830319888734, 40.7578125 ], [ 467.7830319888734, 75.2734375 ], [ 274.37273991655076, 75.2734375 ] ] }, { "title": "VISIONARY USE CASES - THE LONG-TERM HORIZON", "heading_level": null, "page_id": 20, "polygon": [ [ 32.89794921875, 207.13772455089818 ], [ 227.894297635605, 207.13772455089818 ], [ 227.894297635605, 228.90219560878242 ], [ 32.89794921875, 228.90219560878242 ] ] }, { "title": "HUMANOID ROBOT OEMS\nBuild the data flywheel and industrialize the platform", "heading_level": null, "page_id": 20, "polygon": [ [ 274.2373046875, 351.03125 ], [ 470.78164116828924, 351.03125 ], [ 470.78164116828924, 386.5069860279441 ], [ 274.2373046875, 386.5069860279441 ] ] }, { "title": "COMPONENT SUPPLIERS (AUTOMOTIVE, \nINDUSTRIAL, ELECTRONICS, SEMICONDUCTOR)\nDefine your role early and co-develop the humanoid \nsupply chain", "heading_level": null, "page_id": 21, "polygon": [ [ 33.95068359375, 376.734375 ], [ 263.6334533691406, 376.734375 ], [ 263.6334533691406, 427.0047607421875 ], [ 32.89794921875, 427.0047607421875 ] ] }, { "title": "INDUSTRIAL EQUIPMENT AND ROBOTICS \nPLAYERS", "heading_level": null, "page_id": 22, "polygon": [ [ 34.2138671875, 208.1953125 ], [ 225.45626831054688, 208.1953125 ], [ 225.45626831054688, 232.1204833984375 ], [ 34.2138671875, 232.1204833984375 ] ] }, { "title": "Position early in the humanoid manufacturing and \nautomation ecosystem", "heading_level": null, "page_id": 22, "polygon": [ [ 33.42431640625, 234.6328125 ], [ 254.72537231445312, 234.6328125 ], [ 254.72537231445312, 258.0047607421875 ], [ 33.42431640625, 258.0047607421875 ] ] }, { "title": "OPERATORS", "heading_level": null, "page_id": 22, "polygon": [ [ 32.89794921875, 651.0234375 ], [ 92.25350189208984, 649.5546875 ], [ 92.25350189208984, 661.1255187988281 ], [ 32.89794921875, 661.1255187988281 ] ] }, { "title": "Identify use cases early and shape the emerging \nhumanoid ecosystem", "heading_level": null, "page_id": 22, "polygon": [ [ 34.61809539794922, 663.5078125 ], [ 248.95071411132812, 662.0390625 ], [ 248.95071411132812, 687.0047378540039 ], [ 34.61809539794922, 687.0047378540039 ] ] }, { "title": "Data-for-discount models:", "heading_level": null, "page_id": 23, "polygon": [ [ 33.6875, 455.6796875 ], [ 154.09906005859375, 455.6796875 ], [ 154.09906005859375, 466.0082702636719 ], [ 33.6875, 466.0082702636719 ] ] }, { "title": "Conditional commitments:", "heading_level": null, "page_id": 23, "polygon": [ [ 34.2138671875, 611.3671875 ], [ 152.65701293945312, 611.3671875 ], [ 152.65701293945312, 622.0082550048828 ], [ 34.2138671875, 622.0082550048828 ] ] }, { "title": "Choice of partners themselves:", "heading_level": null, "page_id": 23, "polygon": [ [ 274.50048828125, 247.1171875 ], [ 415.69635009765625, 245.6484375 ], [ 415.69635009765625, 258.0082702636719 ], [ 273.44775390625, 258.0082702636719 ] ] }, { "title": "AI COMPANIES", "heading_level": null, "page_id": 23, "polygon": [ [ 275.02685546875, 428.5078125 ], [ 344.8191223144531, 428.5078125 ], [ 344.8191223144531, 440.12554931640625 ], [ 275.02685546875, 440.12554931640625 ] ] }, { "title": "Extend AI leadership into physical AI \nand robotics platforms", "heading_level": null, "page_id": 23, "polygon": [ [ 276.5815124511719, 443.9296875 ], [ 437.2340393066406, 442.4609375 ], [ 437.2340393066406, 466.0047607421875 ], [ 276.3427734375, 466.0047607421875 ] ] }, { "title": "EUROPE AND THE MIDDLE EAST IN THE \nHUMANOID ROBOTICS RACE", "heading_level": null, "page_id": 24, "polygon": [ [ 33.6875, 107.953125 ], [ 214.44114685058594, 107.953125 ], [ 214.44114685058594, 131.36083984375 ], [ 33.6875, 131.36083984375 ] ] }, { "title": "Conclusion", "heading_level": null, "page_id": 25, "polygon": [ [ 33.42431640625, 40.0234375 ], [ 200.99501037597656, 38.5546875 ], [ 200.99501037597656, 72.81536865234375 ], [ 32.37158203125, 72.81536865234375 ] ] }, { "title": "Credits", "heading_level": null, "page_id": 26, "polygon": [ [ 33.57699966430664, 41.125 ], [ 144.56199645996094, 39.65625 ], [ 144.56199645996094, 72.81536865234375 ], [ 33.1611328125, 72.81536865234375 ] ] }, { "title": "AUTHORS", "heading_level": null, "page_id": 26, "polygon": [ [ 33.1611328125, 208.9296875 ], [ 79.35890197753906, 207.4609375 ], [ 79.35890197753906, 219.12451171875 ], [ 33.1611328125, 219.12451171875 ] ] }, { "title": "Thomas Kirschstein", "heading_level": null, "page_id": 26, "polygon": [ [ 34.01570129394531, 235.3671875 ], [ 124.748291015625, 233.8984375 ], [ 124.748291015625, 245.12454223632812 ], [ 33.6875, 245.12454223632812 ] ] }, { "title": "Jonas Zinn", "heading_level": null, "page_id": 26, "polygon": [ [ 34.01570129394531, 286.7734375 ], [ 85.29949951171875, 285.3046875 ], [ 85.29949951171875, 297.1175537109375 ], [ 33.42431640625, 297.1175537109375 ] ] }, { "title": "Shuai Shi", "heading_level": null, "page_id": 26, "polygon": [ [ 34.01570129394531, 338.9140625 ], [ 77.87720489501953, 337.4453125 ], [ 77.87720489501953, 349.11053466796875 ], [ 33.1611328125, 349.11053466796875 ] ] 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