Open world embodied intelligence: Learning from perception to action in the wild

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  • Date
    22 September 2026
    Timeframe
    16:00 - 17:00 CEST, Geneva
    Duration
    1 hour

      A longstanding goal in robotics is to build agents that learn from the world and assist people in everyday tasks across homes, factories, and streets. This talk outlines a path to open world autonomy that learns continuously, reasons with language and vision, and closes the loop from perception to action. The speaker will present representations that capture objects, relations, and articulation, online learning that adapts during deployment without forgetting, and uncertainty-aware decision making that knows when to ask for clarification, seek information, or recover. The speaker will also discuss data and model efficiency in policy learning for long-horizon tasks, including demonstrations, point clouds, and world models for rapid offline adaptation. The talk will conclude with a discussion of safety, fairness, and responsible deployment, so that learning-enabled autonomy earns trust and delivers value to society. 

      Recommended mastery level : Intermediate level in Robotics and AI.

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