F2F-AP: Flow-to-Future Asynchronous Policy for Real-time Dynamic Manipulation
The Flow-to-Future Asynchronous Policy (F2F-AP) addresses latency in robotic manipulation by predicting future object states using predicted flow and aligning these predictions with real future data via contrastive learning. This allows the policy to proactively plan and execute actions that compensate for system delays, significantly improving responsiveness and success rates in dynamic tasks.