NoMad: Goal Masked Diffusion Policies for Navigation and Exploration

摘要

We introduce NoMad, a goal-masked diffusion policy for robot navigation and exploration. Our approach uses conditional diffusion models with goal masking to enable robots to navigate to diverse goals in unseen environments, combining the generative power of diffusion models with flexible goal-conditioning for robust autonomous navigation.