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 dynamics. Researchers at BAIR added stochasticity to improve robustness. These improvements allow agents to plan complex sequences without the computational collapse typical of standard gradient-based methods.