Tactile VLAExpert
SimpleTouch: Can Vision-Language-Action Models Master Contact-Rich Manipulation Without Tactile Policy Pretraining?
SimpleTouch is an arXiv preprint that adds a tactile expert to the π0.5 vision-language-action model, using a frozen pretrained T3 tactile encoder and training only on 50 task demonstrations with future-touch prediction as auxiliary supervision. It reaches 77.5% average success across six UniVTAC contact-rich tasks and 71.3% across four real-robot tasks, outperforming the pretrained tactile policy FTP-1 by 10.8 and 8.8 percentage points. This suggests strong contact-rich manipulation can be learned without costly tactile policy pretraining or explicit visuotactile alignment.