{"id":31885,"date":"2026-03-27T13:47:00","date_gmt":"2026-03-27T12:47:00","guid":{"rendered":"https:\/\/edgecomputing-expo.com\/europe\/?post_type=agenda&p=31885"},"modified":"2026-06-04T20:00:25","modified_gmt":"2026-06-04T18:00:25","slug":"physical-al","status":"publish","type":"agenda","link":"https:\/\/edgecomputing-expo.com\/europe\/agenda\/physical-al\/","title":{"rendered":"Physical AI"},"content":{"rendered":"\t\t
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DAY 2 | FREE TRACK<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Robots, Autonomous Systems, and AI that Acts in the Real World<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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09:45 - 10:00<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Chairperson\u2019s Opening Remarks<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Chairpersons welcome and opening remarks<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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10:00 - 10:40<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Panel: The Physical AI Stack - From Edge Devices to Autonomous Action<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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A macro view of how physical AI systems are structured:<\/p>

  • Edge AI (STBs, sensors, smart cameras)<\/li>
  • Multimodal perception & sensor fusion<\/li>
  • Foundation models for robotics<\/li>
  • Orchestration layers<\/li>
  • Governance & safety<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    10:45 - 11:15<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    Presentation: Physical AI in 2026 - from pilots to scaled fleets<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    What is genuinely new (foundation models, simulation at scale, edge compute), and what still breaks in production.<\/p><\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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    11:20 - 11:50<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    Presentation: When Cities, Vehicles, and Robots Think & Act - The Unified Future of Physical AI<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    Cities are dynamic physical systems with humans, vehicles, sensors, and robots all interdependent. This session positions SDVs and Smart City infrastructure as Physical AI domains with shared challenges \u2013 sensing, prediction, optimization, and safe actuation.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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    11:50 - 12:20<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    Networking Break<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    12:20 - 12:50<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    Presentation: Operating at fleet scale - orchestration, routing, and continuous improvement<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    How large robot fleets are coordinated, monitored, and optimised using AI models, including congestion reduction, routing efficiency, and ops integration.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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    12:55 - 13:15<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    Presentation: SDVs & Physical AI<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    Vehicles aren\u2019t \u201cjust cars\u201d \u2014 they\u2019re mobile AI platforms that perceive city infrastructure, interact with people and machines, and make real-time decisions. This session covers:<\/p>

    Perception stacks in mobility vs robotics<\/p>

    Predictive models for unstructured urban interaction<\/p>

    Sensor fusion between vehicles and infrastructure<\/p>

    Safety, simulation, and regulation parallels with robots<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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    Lunch Break<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    14:15 - 14:55<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    Panel: Robots, Autonomous Systems & the New Embodied Intelligence Stack<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    Join us as we take a deep dive into robotics \u2013 but as part of the bigger ecosystem.<\/p>

    • Robot foundation models<\/li>
    • Vision-language-action systems<\/li>
    • Generalisation challenges<\/li>
    • Build vs buy decisions<\/li>
    • Where humanoids fit (and don\u2019t)<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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      15:00 - 15:20<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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      Presentation: The Economics of Physical AI \u2013 Workforce, ROI & Transformation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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      • Labour displacement vs augmentation<\/li>
      • Tele-ops & human-in-the-loop models<\/li>
      • Measuring ROI properly<\/li>
      • Enterprise adoption timelines<\/li>
      • What becomes autonomous first?<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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        15:25 - 15:45<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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        Presentation: Physical AI in the enterprise - ROI, deployment patterns, and what to measure<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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        Physical AI in the enterprise: ROI, deployment patterns, and what to measure.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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        15:45<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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        Chairperson's Closing Remarks<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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        Chairpersons welcome and opening remarks<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Panel: The Physical AI Stack - From Edge Devices to Autonomous Action","slot_type":"Entry","slot_day":"Same","slot_time":"10:00 - 10:40","slot_alternative_track_type":"","slot_text":"

        A macro view of how physical AI systems are structured:<\/p>\n

          \n
        • Edge AI (STBs, sensors, smart cameras)<\/li>\n
        • Multimodal perception & sensor fusion<\/li>\n
        • Foundation models for robotics<\/li>\n
        • Orchestration layers<\/li>\n
        • Governance & safety<\/li>\n<\/ul>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Presentation: Physical AI in 2026 - from pilots to scaled fleets","slot_type":"Entry","slot_day":"Same","slot_time":"10:45 - 11:15","slot_alternative_track_type":"","slot_text":"

          What is genuinely new (foundation models, simulation at scale, edge compute), and what still breaks in production.<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Presentation: When Cities, Vehicles, and Robots Think & Act - The Unified Future of Physical AI","slot_type":"Entry","slot_day":"Same","slot_time":"11:20 - 11:50","slot_alternative_track_type":"","slot_text":"

          Cities are dynamic physical systems with humans, vehicles, sensors, and robots all interdependent. This session positions SDVs and Smart City infrastructure as Physical AI domains with shared challenges \u2013 sensing, prediction, optimization, and safe actuation.<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Networking Break","slot_type":"Break","slot_day":"Same","slot_time":"11:50 - 12:20","slot_alternative_track_type":"","slot_text":"","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Presentation: Operating at fleet scale - orchestration, routing, and continuous improvement","slot_type":"Entry","slot_day":"Same","slot_time":"12:20 - 12:50","slot_alternative_track_type":"","slot_text":"

          How large robot fleets are coordinated, monitored, and optimised using AI models, including congestion reduction, routing efficiency, and ops integration.<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Presentation: SDVs & Physical AI","slot_type":"Entry","slot_day":"Same","slot_time":"12:55 - 13:15","slot_alternative_track_type":"","slot_text":"

          Vehicles aren\u2019t \u201cjust cars\u201d \u2014 they\u2019re mobile AI platforms that perceive city infrastructure, interact with people and machines, and make real-time decisions. This session covers:<\/p>\n

          Perception stacks in mobility vs robotics<\/p>\n

          Predictive models for unstructured urban interaction<\/p>\n

          Sensor fusion between vehicles and infrastructure<\/p>\n

          Safety, simulation, and regulation parallels with robots<\/p>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Lunch Break","slot_type":"Break","slot_day":"Same","slot_time":"13:15 - 14:15","slot_alternative_track_type":"","slot_text":"","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Panel: Robots, Autonomous Systems & the New Embodied Intelligence Stack","slot_type":"Entry","slot_day":"Same","slot_time":"14:15 - 14:55","slot_alternative_track_type":"","slot_text":"

          Join us as we take a deep dive into robotics \u2013 but as part of the bigger ecosystem.<\/p>\n

            \n
          • Robot foundation models<\/li>\n
          • Vision-language-action systems<\/li>\n
          • Generalisation challenges<\/li>\n
          • Build vs buy decisions<\/li>\n
          • Where humanoids fit (and don\u2019t)<\/li>\n<\/ul>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Presentation: The Economics of Physical AI \u2013 Workforce, ROI & Transformation","slot_type":"Entry","slot_day":"Same","slot_time":"15:00 - 15:20","slot_alternative_track_type":"","slot_text":"
              \n
            • Labour displacement vs augmentation<\/li>\n
            • Tele-ops & human-in-the-loop models<\/li>\n
            • Measuring ROI properly<\/li>\n
            • Enterprise adoption timelines<\/li>\n
            • What becomes autonomous first?<\/li>\n<\/ul>\n","slot_speakers":false,"slot_sponsor":false,"slot_divider":true,"slot_display":true},{"slot_heading":"Presentation: Physical AI in the enterprise - ROI, deployment patterns, and what to measure","slot_type":"Entry","slot_day":"Same","slot_time":"15:25 - 15:45","slot_alternative_track_type":"","slot_text":"

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