dailyai.report

The GRASP planner optimizes trajectories by lifting them into virtual states, allowing parallel optimization across time. This approach solves the vanishing gradient problem common in long-horizon planning. By adding stochasticity directly to trajectories, BAIR researchers improved stability in learned dynamics. Practitioners can now execute complex, multi-step plans without the typical computational collapse.