TacDyn-WAM: Learning Implicit Tactile Dynamics in a Heterogeneous Visuo-Tactile World Action Model
TacDyn-WAM is a world action model that predicts future contact evolution by learning implicit tactile dynamics instead of reconstructing pixel data. It uses two experts—one for vision and one for tactile prediction in a specialized space called TacRep—to enable one-pass multi-horizon prediction without iterative denoising, leading to state-of-the-art performance on robotic manipulation tasks.