F2F-AP combines predicted object flow with contrastive feature alignment to give asynchronous policies proactive visual context for latency compensation in dynamic manipulation.
UMI on Legs: Making Manipulation Policies Mo- bile with Manipulation-Centric Whole-body Controllers
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F2F-AP: Flow-to-Future Asynchronous Policy for Real-time Dynamic Manipulation
F2F-AP combines predicted object flow with contrastive feature alignment to give asynchronous policies proactive visual context for latency compensation in dynamic manipulation.