The GRASP planner optimizes trajectories by lifting them into virtual states. This approach allows parallel optimization across time and integrates stochasticity directly into the process. Researchers at BAIR developed the method to overcome the computational bottlenecks of traditional gradient-based planning. It allows agents to navigate complex environments over significantly longer time horizons.