The GRASP planner optimizes trajectories by lifting them into virtual states for parallel processing across time. This approach solves the vanishing gradient problem common in long-horizon dynamics. Researchers at BAIR added stochasticity directly to the planning process to improve robustness. Practitioners can now execute more complex, multi-step tasks without the usual optimization collapse.