Temporal manipulationIntermediate
PhasePlan: Ordered Future-Phase Planning for Robot Brain Models
This preprint introduces PhasePlan, an ordered future-phase planning method for robot brain models. On a real-robot conveyor sorting task with a pretrained π0.5 backbone, PhasePlan reduces offline joint-action error by 22.5% relative to the original policy and reaches 92.5% per-position phase accuracy. By preserving where phase transitions occur within each 16-step action chunk, it may improve action timing in dynamic manipulation tasks.