Robot policies stop reading only the current frame: optical-flow supervision predicts future motion, and a 0.87B model averages 63.3% on real dual-arm tasks
Evo-World adds optical-flow-supervised future motion prediction to a lightweight vision-language-action policy, reaching 91.1% tier-averaged success on Meta-World MT50, a 13.0% relative gain over the non-predictive baseline, and beating the evaluated baselines on AgileX single-arm and bimanual tasks with 0.87B parameters.