Masked Generative Motion Planning with Geometry-Guided Token Search
Masked Generative Motion Planning (MGMP) extends learned trajectory priors from initial generation to structural repair by treating motion planning as masked generation over discrete tokens. Geometry-Guided Token Search (GGTS) uses scene geometry to intelligently guide where to edit and what alternatives to test, enabling route-level restructuring beyond simple local adjustments.