Mukund Mitra- Towards Physical AI: Time-Series Prediction for Intent-Aware Robot Learning

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• Speaker to be confirmed
• Tuesday 05 August 2025, 12:00-13:00
• Cambridge University Engineering Department, JDB Seminar Room.

If you have a question about this talk, please contact Melanie Ellwood.

Understanding human intent is fundamental to robots that can collaborate naturally and effectively. Intent prediction involves forecasting time-series data – such as human motion trajectories, gaze patterns, and interaction data – to enable machines to anticipate human actions, respond appropriately, and learn from interaction. This capability paves the way for safer, faster, and intuitive human-robot collaboration. This work presents a framework that combines Imitation Learning techniques with Foundation Models to advance intent-aware robot learning. The approach is demonstrated across diverse tasks, including target prediction in extended reality, human-robot handovers, and multi-robot coordination. By leveraging multimodal cues—such as hand motion, gaze, and interaction history – the system enhances prediction accuracy. Additionally, large language and vision models enable the interpretation of high-level human instructions for task planning and robot navigation. Together, these contributions move toward the goal of Physical AI, where robots can learn from humans and understand and act on their intent in real-world environments.

This talk is part of the Probabilistic Systems, Information, and Inference Group Seminars series.

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