Physical Time as a Missing Dimension of Robot Policy Memory
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Source roundup from published reports. Claims below are attributed to their publishers, not independently verified. arXiv Robotics — research abstracts: Physical Time as a Missing Dimension of Robot Policy Memory Dynamics. This research introduces Temporal Flow Policy (TFP), which models robot policy memory by incorporating physical time as a critical dimension. TFP learns memory dynamics to retain past events and evolve memory states over…
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- arXiv Robotics — research abstractsPhysical Time as a Missing Dimension of Robot Policy Memory Dynamics
This research introduces Temporal Flow Policy (TFP), which models robot policy memory by incorporating physical time as a critical dimension. TFP learns memory dynamics to retain past events and evolve memory states over measured time intervals. The approach outperforms existing methods in tasks requiring timing and memory, demonstrating the importance of temporal awareness in embodied AI.
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