UGE-TO models trajectories as uncertainty-induced distributions and uses Hellinger distance to enforce sample diversity, yielding faster convergence and better success rates in sampling-based MPC.
Gusto: Guaranteed sequential trajectory optimization via sequential convex programming
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Uncertainty Guided Exploratory Trajectory Optimization for Sampling-Based Model Predictive Control
UGE-TO models trajectories as uncertainty-induced distributions and uses Hellinger distance to enforce sample diversity, yielding faster convergence and better success rates in sampling-based MPC.