Open-sourcing AI Habitat, an advanced simulation platform for embodied AI research

From a robot asked to "grab my phone from the desk upstairs" to a device that helps its visually impaired wearer navigate an unfamiliar subway system, the next generation of AI-powered assistants will need to demonstrate a broad range of abilities. Many researchers believe the most effective way to develop these skills is to focus on embodied AI, which uses interactive environments to ground systems' training in the real world, rather than relying on static data sets. To accelerate progress in this space, we're sharing AI Habitat, a new simulation platform created by Facebook AI that's designed to train embodied agents (such as virtual robots) in photo-realistic 3D environments. Our goal in sharing AI Habitat is to provide the most universal simulator to date for embodied research, with an open, modular design that's both powerful and flexible enough to bring reproducibility and standardized benchmarks to this subfield. To illustrate the benefits of this new platform, we're also sharing Replica, a data set of hyperrealistic 3D reconstructions of a staged apartment, retail store, and other indoor spaces that were generated by a group of scientists within Facebook Reality Labs (FRL).