What if the next leap in robot manipulation comes from touch, not just vision?
To get there, foundation models need to understand tactile feedback the way they understand images and language. And tactile policies cannot be locked to specific hardware (that makes real-world deployments & maintenance quite complicated).
FTP-1 solves both. One of the 1st foundation model for touch. 21 sensors. ~3,000 hours of data. Transfers to hardware it has never seen before.
+17% on known hardware. +31% on never-seen hardware.
We're proud this research led by @michaelyuancb ran on #SharpaNorth, #SharpaWave hands, and our DTC sensors.
Special thanks to the teams at @Tsinghua_Uni , @UCBerkeley , @ETH , and @sjtu1896.
Project page: https://t.co/07BckCfoPj