Social NavigationIntermediate
Social-WM: Safety-Aware Latent World Models for Robot Social Navigation
Social-WM is a preprint describing a latent world-model planner for robot social navigation that learns future latent states and action realizability from egocentric RGB video. On Social-HM3D it reaches 63.77% success while reducing human collisions to 21.67%, and transfers zero-shot to Social-MP3D. This matters because it improves pedestrian safety without explicit pedestrian tracking, privileged human state, or online reinforcement learning.