AI Habitat is an open-source simulation platform from Meta AI Research for embodied AI research. It provides high-performance 3D simulated environments for training and evaluating AI agents on navigation, manipulation, and human-robot collaboration tasks. Habitat-Sim delivers 10,000+ FPS simulation and Habitat-Lab provides a modular library for defining tasks, training agents, and running benchmarks.
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Run: Capabilities Using Naftiko
- Artificial Intelligence, Simulation, Embodied AI, Robotics, Computer Vision, Reinforcement Learning, Machine Learning, Open Source, Research
- Created: 2025-02-17
- Modified: 2026-04-19
AI Habitat simulation framework for embodied AI research, including Habitat-Sim (high-performance 3D simulator) and Habitat-Lab (modular training library). Supports navigation, manipulation, and human-robot collaboration tasks across photorealistic 3D indoor environments.
Human URL: https://aihabitat.org/
- Embodied AI, Simulation, Robotics, Python, Computer Vision, Reinforcement Learning
- Documentation
- API Documentation
- Habitat-Sim GitHub
- Habitat-Lab GitHub
- Habitat-Sim Python Package
- Habitat-Lab Python Package
- AI Habitat GitHub Organization
- Habitat-Sim Repository
- Habitat-Lab Repository
- Habitat Documentation
- Habitat Challenge
- Habitat Discussions
- Habitat HuggingFace
- Python Package (habitat-sim)
- Python Package (habitat-lab)
- PARTNR Planner
| Name | Description |
|---|---|
| High-Performance Simulation | Habitat-Sim achieves 10,000+ FPS on a single GPU and 8,000+ steps/second for robot simulation, enabling fast RL training. |
| Photorealistic 3D Environments | Supports HM3D, MatterPort3D, Gibson, Replica, and HSSD datasets with high visual fidelity. |
| Physics-Enabled Simulation | Bullet physics engine integration for realistic object interactions and manipulation tasks. |
| Robot Support via URDF | Configurable robot models including Fetch mobile manipulator, Franka arm, and AlienGo quadruped. |
| Configurable Sensors | RGB, depth, semantic, and egomotion sensors for varied agent perception configurations. |
| Modular Task Framework | Habitat-Lab provides modular task definition, agent configuration, and benchmarking tools. |
| Imitation and Reinforcement Learning | Built-in support for IL and RL training pipelines for embodied AI agents. |
| Human-Robot Collaboration | Habitat 3.0 co-habitat supports humans, avatars, and robots sharing simulated environments. |
| Parallelizable Across Clusters | Designed for large-scale distributed training across GPU clusters. |
| Annual Benchmark Challenge | Habitat Challenge on EvalAI provides standardized evaluation of navigation and manipulation agents. |
| Name | Description |
|---|---|
| Embodied Navigation Research | Train and evaluate AI agents on point-goal, object-goal, and image-goal navigation tasks in 3D environments. |
| Robot Manipulation Research | Develop manipulation skills for pick-and-place, rearrangement, and tool use with simulated robot arms. |
| Human-Robot Collaboration | Research human-robot teaming for household tasks using the PARTNR benchmark and Habitat 3.0. |
| Reinforcement Learning Training | Fast simulation enables RL agents to explore millions of environment steps for policy learning. |
| Dataset Creation and Annotation | Generate synthetic data, annotations, and demonstrations for embodied AI training datasets. |
| Name | Description |
|---|---|
| PyTorch | Deep learning framework integration for neural network training and inference. |
| HuggingFace | Datasets and models available on HuggingFace Hub at ai-habitat organization. |
| EvalAI | Habitat Challenge evaluation hosted on EvalAI platform for standardized benchmarking. |
| Conda / conda-forge | Conda package distribution via conda-forge and aihabitat channels. |
| Bullet Physics | Bullet physics engine for realistic rigid-body simulation and manipulation. |
| ROS | Robot Operating System integration for sim-to-real transfer research. |
Machine-readable schema specifications organized by format.
- ai-habitat-agent-config-schema.json
- ai-habitat-agent-observation-schema.json
- ai-habitat-episode-schema.json
- ai-habitat-navigation-goal-schema.json
- ai-habitat-observation-schema.json
- ai-habitat-sensor-spec-schema.json
- ai-habitat-simulator-config-schema.json
- ai-habitat-task-config-schema.json
- ai-habitat-agent-config-structure.json
- ai-habitat-agent-observation-structure.json
- ai-habitat-episode-structure.json
- ai-habitat-navigation-goal-structure.json
- ai-habitat-observation-structure.json
- ai-habitat-sensor-spec-structure.json
- ai-habitat-simulator-config-structure.json
- ai-habitat-task-config-structure.json
- ai-habitat-agent-config-example.json
- ai-habitat-agent-observation-example.json
- ai-habitat-episode-example.json
- ai-habitat-navigation-goal-example.json
- ai-habitat-observation-example.json
- ai-habitat-sensor-spec-example.json
- ai-habitat-simulator-config-example.json
- ai-habitat-task-config-example.json
- AI Habitat Vocabulary — Unified taxonomy mapping 7 resources, 5 actions, 1 workflow, and 2 personas across simulation and embodied AI task dimensions
FN: Kin Lane
Email: kin@apievangelist.com