Disney Research

Creating animations for robotic characters is very challenging due to the constraints imposed by their physical nature. In particular, the combination of fast motions and unavoidable structural deformations leads to mechanical oscillations that negatively affect their performances. Our goal is to automatically transfer motions created using traditional animation software to robotic characters while avoiding such artifacts.

In this paper, we propose a trajectory-based reinforcement learning method named deep latent policy gradient (DLPG) for learning locomotion skills.

Tactile effects are created using directable water jets that spray onto the rear of a flexible screen, with different nozzles for different firework effects.