# facebookresearch/habitat-lab **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/facebookresearch-habitat-lab).** 2,848 stars · 633 forks · Python · mit ## Links - GitHub: https://github.com/facebookresearch/habitat-lab - Homepage: https://aihabitat.org/ - awesome-repositories: https://awesome-repositories.com/repository/facebookresearch-habitat-lab.md ## Topics `ai` `computer-vision` `deep-learning` `deep-reinforcement-learning` `python` `reinforcement-learning` `research` `robotics` `sim2real` `simulator` ## Description Habitat-Lab is an open-source platform for training and evaluating embodied AI agents in photorealistic 3D indoor environments. It functions as a high-performance 3D indoor environment simulator that supports physics-based interaction, enabling research into navigation and manipulation tasks. The platform provides a modular task-environment abstraction that separates task logic from environment simulation, using configuration-driven pipeline assembly to compose simulation and training pipelines. It includes a hierarchical sensor-actuator architecture for mixing and matching perception and action components per task, along with dataset-centric task loading that defines scene configurations, object placements, and success criteria. The system offers interactive agent visualization through top-down maps, 3D scene views, and step-by-step task execution in notebooks, as well as a ROS integration bridge for connecting the simulation to external robotics frameworks. The platform supports training agents using PPO-based reinforcement learning with vectorized environments and reward shaping, and provides pre-built baseline integrations for embodied AI tasks. It also enables virtual robot teleoperation through keyboard controls for manual testing and exploration. ## Tags ### Part of an Awesome List - [Embodied AI Platforms](https://awesome-repositories.com/f/awesome-lists/ai/embodied-ai-platforms.md) — Provides an integrated platform for training and evaluating embodied AI agents in photorealistic 3D indoor environments. - [Embodied Agents](https://awesome-repositories.com/f/awesome-lists/ai/embodied-agents.md) — Trains agents to perform navigation and manipulation tasks inside simulated indoor environments. ([source](https://aihabitat.org/docs/)) - [Reinforcement Learning Frameworks](https://awesome-repositories.com/f/awesome-lists/ai/reinforcement-learning-frameworks.md) — Provides PPO-based training pipelines and benchmark tasks for developing navigation and manipulation agents. - [Simulation Environment Libraries](https://awesome-repositories.com/f/awesome-lists/ai/simulation-environments/simulation-environment-libraries.md) — Provides access to core simulation components for environments, tasks, datasets, and simulators to benchmark agent performance. ([source](https://aihabitat.org/docs/)) - [Interactive 3D Simulators](https://awesome-repositories.com/f/awesome-lists/ai/simulation-environments/simulation-environment-libraries/indoor-scene-libraries/interactive-3d-simulators.md) — A high-performance simulator that renders realistic indoor scenes and supports physics-based interaction for embodied AI research. - [Modular Sensor-Actuator Frameworks](https://awesome-repositories.com/f/awesome-lists/devtools/sensor-and-actuator-drivers/modular-sensor-actuator-frameworks.md) — Organizes agent perception and action into modular sensor and actuator classes that can be mixed and matched per task. - [ROS Simulation Bridges](https://awesome-repositories.com/f/awesome-lists/data/physics-and-simulation/robotic-physics-and-sensor-simulators/ros-simulation-bridges.md) — Connects the 3D simulator to external robotics frameworks through a ROS interface for real-time control and sensor feedback. - [ROS Simulation Bridges](https://awesome-repositories.com/f/awesome-lists/devtools/robotics-simulators/ros-simulation-bridges.md) — Bridges simulation with the Robot Operating System for physics-based robotics development and asset access. ([source](https://cdn.jsdelivr.net/gh/facebookresearch/habitat-lab@main/README.md)) - [Rearrangement](https://awesome-repositories.com/f/awesome-lists/ai/rearrangement.md) — Trains home assistants to rearrange objects within their habitat. - [Sim to Real Transfer](https://awesome-repositories.com/f/awesome-lists/ai/sim-to-real-transfer.md) — Provides infrastructure for training and deploying embodied agents. ### Artificial Intelligence & ML - [Reinforcement Learning Integrations](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/machine-learning-training/pipelines-and-orchestration/training-orchestration-systems/training-methodologies/reinforcement-learning-integrations.md) — Provides pre-built PPO training loops with vectorized environments and reward shaping for embodied AI tasks. - [Reinforcement Learning Training](https://awesome-repositories.com/f/artificial-intelligence-ml/reinforcement-learning-training.md) — Trains agents on embodied AI tasks using PPO-based reinforcement learning with provided baselines. ([source](https://cdn.jsdelivr.net/gh/facebookresearch/habitat-lab@main/README.md)) ### Data & Databases - [Embodied AI Task Loaders](https://awesome-repositories.com/f/data-databases/dataset-loading/embodied-ai-task-loaders.md) — Loads embodied AI tasks from structured dataset files defining scene configurations, object placements, and success criteria. - [Agent Behavior Visualizers](https://awesome-repositories.com/f/data-databases/interactive-visualization-rendering/agent-behavior-visualizers.md) — Renders top-down maps, agent trajectories, and 3D scene views using off-screen rendering and matplotlib integration. ### Development Tools & Productivity - [Registry-Based Component Loaders](https://awesome-repositories.com/f/development-tools-productivity/workflow-automation-tools/build-task-automation/external-task-orchestrators/modular-task-configurations/registry-based-component-loaders.md) — Separates task logic from environment simulation using interchangeable configuration files and registry-based component loading. - [Robotics System Integrations](https://awesome-repositories.com/f/development-tools-productivity/external-command-integrations/robotics-system-integrations.md) — Connects Habitat simulation to ROS for physics-based robotics development and real-time asset access. - [Habitat-ROS Bridges](https://awesome-repositories.com/f/development-tools-productivity/external-command-integrations/robotics-system-integrations/habitat-ros-bridges.md) — Provides a bridge connecting Habitat simulation to the Robot Operating System for robotics development and testing. ### Software Engineering & Architecture - [Configuration-Driven Pipelines](https://awesome-repositories.com/f/software-engineering-architecture/configuration-driven-pipelines.md) — Builds simulation and training pipelines by composing YAML configuration files that specify sensors, actuators, and task parameters. ### System Administration & Monitoring - [Agent Behavior Visualizers](https://awesome-repositories.com/f/system-administration-monitoring/interactive-agent-execution/agent-behavior-visualizers.md) — Explores agent behavior through top-down maps, 3D environment views, and step-by-step task execution in notebooks. ### User Interface & Experience - [Interactive AI Demos](https://awesome-repositories.com/f/user-interface-experience/interactive-ai-demos.md) — Runs interactive tutorials and notebooks to demonstrate agent behavior and explore 3D environments. ([source](https://aihabitat.org/docs/)) - [Keyboard-Controlled Agent Demos](https://awesome-repositories.com/f/user-interface-experience/interactive-ai-demos/keyboard-controlled-agent-demos.md) — Ships interactive keyboard-controlled agent demos for manual testing and exploration of 3D environments.