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F2F-AP: Flow-to-Future Asynchronous Policy for Real-time Dynamic Manipulation
Asynchronous inference has emerged as a prevalent paradigm in robotic manipulation, achieving significant progress in ensuring trajectory smoothness and efficiency. However, a systemic challenge remains unresolved, as inherent latency causes generated actions to inevitably lag behind the real-time e
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