dailyai.report

The GRASP planner optimizes trajectories by lifting them into virtual states, allowing parallel optimization across time. This approach solves the instability typical of gradient-based planning in learned dynamics. By adding stochasticity directly to the trajectory, it prevents local minima. Practitioners can now execute complex, long-term plans without the usual computational collapse.