MoMo: Dial Motion Mode in Robot Manipulation with Spatiotemporal Action Tokenization

Researchers developed MoMo, a two-stage imitation-learning framework that enables robots to adapt their manipulation behaviors across different tasks by varying a continuous motion-mode condition. MoMo produces distinct motion styles and can transfer unseen modes to new tasks while maintaining success rates, demonstrating compositional generalization in robot manipulation.