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We present Habitat 3.0: a simulation platform for studying collaborativehuman-robot tasks in home environments. Habitat 3.0 offers contributions acrossthree dimensions: (1) Accurate humanoid simulation: addressing challenges inmodeling complex deformable bodies and diversity in appearance and motion, allwhile ensuring high simulation speed. (2) Human-in-the-loop infrastructure:enabling real human interaction with simulated robots via mouse/keyboard or aVR interface, facilitating evaluation of robot policies with human input. (3)Collaborative tasks: studying two collaborative tasks, Social Navigation andSocial Rearrangement. Social Navigation investigates a robot's ability tolocate and follow humanoid avatars in unseen environments, whereas SocialRearrangement addresses collaboration between a humanoid and robot whilerearranging a scene. These contributions allow us to study end-to-end learnedand heuristic baselines for human-robot collaboration in-depth, as well asevaluate them with humans in the loop. Our experiments demonstrate that learnedrobot policies lead to efficient task completion when collaborating with unseenhumanoid agents and human partners that might exhibit behaviors that the robothas not seen before. Additionally, we observe emergent behaviors duringcollaborative task execution, such as the robot yielding space when obstructinga humanoid agent, thereby allowing the effective completion of the task by thehumanoid agent. Furthermore, our experiments using the human-in-the-loop tooldemonstrate that our automated evaluation with humanoids can provide anindication of the relative ordering of different policies when evaluated withreal human collaborators. Habitat 3.0 unlocks interesting new features insimulators for Embodied AI, and we hope it paves the way for a new frontier ofembodied human-AI interaction capabilities.

Habitat 3.0: A Co-Habitat for Humans, Avatars and Robots