aid: ai-habitat url: >- https://raw.githubusercontent.com/api-evangelist/ai-habitat/refs/heads/main/apis.yml apis: - aid: ai-habitat:ai-habitat name: AI Habitat tags: - Embodied AI - Simulation - Robotics - Python - Computer Vision - Reinforcement Learning humanURL: 'https://aihabitat.org/' properties: - url: https://aihabitat.org/ type: Documentation - url: https://aihabitat.org/docs/ type: Documentation title: API Documentation - url: https://github.com/facebookresearch/habitat-sim type: GitHubRepository title: Habitat-Sim GitHub - url: https://github.com/facebookresearch/habitat-lab type: GitHubRepository title: Habitat-Lab GitHub - url: https://pypi.org/project/habitat-sim/ type: SDK title: Habitat-Sim Python Package - url: https://pypi.org/project/habitat-lab/ type: SDK title: Habitat-Lab Python Package description: >- 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. name: AI Habitat tags: - Artificial Intelligence - Simulation - Embodied AI - Robotics - Computer Vision - Reinforcement Learning - Machine Learning - Open Source - Research kind: contract image: https://kinlane-productions.s3.amazonaws.com/apis-json/apis-json-logo.jpg access: 3rd-Party created: '2025-02-17' modified: '2026-04-19' position: Consuming description: >- 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. maintainers: - FN: Kin Lane email: kin@apievangelist.com specificationVersion: '0.19' common: - name: AI Habitat GitHub Organization url: https://github.com/facebookresearch type: GitHubOrganization description: Meta AI Research GitHub organization hosting Habitat repositories. - name: Habitat-Sim Repository url: https://github.com/facebookresearch/habitat-sim type: GitHubRepository description: High-performance 3D simulator for embodied AI research (C++/Python). - name: Habitat-Lab Repository url: https://github.com/facebookresearch/habitat-lab type: GitHubRepository description: Modular library for embodied AI task definition, training, and benchmarking. - name: Habitat Documentation url: https://aihabitat.org/docs/ type: Documentation description: Official documentation for AI Habitat platform. - name: Habitat Challenge url: https://aihabitat.org/challenge/ type: Portal description: Annual Habitat Challenge competition on EvalAI for embodied AI navigation. - name: Habitat Discussions url: https://github.com/facebookresearch/habitat-lab/discussions type: Forum description: Community forum for Habitat questions and support. - name: Habitat HuggingFace url: https://huggingface.co/ai-habitat type: Portal description: AI Habitat datasets and models on HuggingFace. - name: Habitat-Sim PyPI url: https://pypi.org/project/habitat-sim/ type: SDK title: Python Package (habitat-sim) description: Install Habitat-Sim via pip or conda. - name: Habitat-Lab PyPI url: https://pypi.org/project/habitat-lab/ type: SDK title: Python Package (habitat-lab) description: Install Habitat-Lab via pip. - name: PARTNR Planner url: https://github.com/facebookresearch/partnr-planner type: Tools description: PARTNR benchmark for human-robot collaboration using Large Planning Models with Habitat. - type: Features data: - name: High-Performance Simulation description: Habitat-Sim achieves 10,000+ FPS on a single GPU and 8,000+ steps/second for robot simulation, enabling fast RL training. - name: Photorealistic 3D Environments description: Supports HM3D, MatterPort3D, Gibson, Replica, and HSSD datasets with high visual fidelity. - name: Physics-Enabled Simulation description: Bullet physics engine integration for realistic object interactions and manipulation tasks. - name: Robot Support via URDF description: Configurable robot models including Fetch mobile manipulator, Franka arm, and AlienGo quadruped. - name: Configurable Sensors description: RGB, depth, semantic, and egomotion sensors for varied agent perception configurations. - name: Modular Task Framework description: Habitat-Lab provides modular task definition, agent configuration, and benchmarking tools. - name: Imitation and Reinforcement Learning description: Built-in support for IL and RL training pipelines for embodied AI agents. - name: Human-Robot Collaboration description: Habitat 3.0 co-habitat supports humans, avatars, and robots sharing simulated environments. - name: Parallelizable Across Clusters description: Designed for large-scale distributed training across GPU clusters. - name: Annual Benchmark Challenge description: Habitat Challenge on EvalAI provides standardized evaluation of navigation and manipulation agents. - type: UseCases data: - name: Embodied Navigation Research description: Train and evaluate AI agents on point-goal, object-goal, and image-goal navigation tasks in 3D environments. - name: Robot Manipulation Research description: Develop manipulation skills for pick-and-place, rearrangement, and tool use with simulated robot arms. - name: Human-Robot Collaboration description: Research human-robot teaming for household tasks using the PARTNR benchmark and Habitat 3.0. - name: Reinforcement Learning Training description: Fast simulation enables RL agents to explore millions of environment steps for policy learning. - name: Dataset Creation and Annotation description: Generate synthetic data, annotations, and demonstrations for embodied AI training datasets. - type: Integrations data: - name: PyTorch description: Deep learning framework integration for neural network training and inference. - name: HuggingFace description: Datasets and models available on HuggingFace Hub at ai-habitat organization. - name: EvalAI description: Habitat Challenge evaluation hosted on EvalAI platform for standardized benchmarking. - name: Conda / conda-forge description: Conda package distribution via conda-forge and aihabitat channels. - name: Bullet Physics description: Bullet physics engine for realistic rigid-body simulation and manipulation. - name: ROS description: Robot Operating System integration for sim-to-real transfer research.