Article

ZAP: Pretraining handles understanding, simulation training teaches robot motion

The authors propose Zero-real Agent Policy (ZAP), which uses a pretrained 27B-parameter vision-language model with a simple tool interface to control a robot, trained via supervised fine-tuning and GRPO on simple simulated tasks, without using any real robot data during training.

Part of the event: ZAP: Training Robot Policies Without Real Data

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