Habitat-Sim — High-Performance 3D Embodied AI Simulator
Meta FAIR's C++/Python 3D simulator for embodied AI: 10,000+ SPS, photorealistic rendering, RGB-D/semantic sensors.
Habitat-Sim — High-Performance 3D Embodied AI Simulator
Habitat-Sim is Meta FAIR's high-performance 3D simulator for embodied AI research, underpinning Habitat-Lab. It renders photorealistic indoor scenes (Matterport3D, HM3D, Replica) with RGB, depth, and semantic sensors at 10,000+ frames-per-second on a GPU — orders of magnitude faster than Gazebo or Unity for RL training.
Key features
- 10,000+ SPS on a single GPU for massively parallel training
- Semantic instance / panoptic segmentation sensor
- Physics simulation via Bullet: rigid body, articulated robot control
- Loads URDF robots (Fetch, Spot, Stretch, LoCoBot, Franka)
- Python and C++ APIs; headless rendering on SLURM cluster nodes
Quick start
conda install habitat-sim -c conda-forge -c aihabitat
import habitat_sim
sim_cfg = habitat_sim.SimulatorConfiguration()
sim_cfg.scene_id = "path/to/scene.glb"
agent_cfg = habitat_sim.agent.AgentConfiguration()
sim = habitat_sim.Simulator(habitat_sim.Configuration(sim_cfg, [agent_cfg]))
obs = sim.reset()
print(obs.keys()) # ['color_sensor', 'depth_sensor', 'semantic_sensor']
npx ai-supply add habitat-sim-3d-simulator
Curated mirror of the open-source Habitat-Sim (MIT). Get it from the source.
Compromise signals — malicious or tampered code (leaked secrets, backdoors, a dropped executable) — reduce the score, and known dependency CVEs carry a bounded penalty (they warrant review but never QUARANTINE — update the dependency to clear). Other dangerous-by-capability traits are risk surface, expected for some capabilities. Every finding is mapped to its OWASP control below.
Findings mapped to the OWASP Top 10 for LLM Applications (2025) and the OWASP Machine Learning Security Top 10. Expand any flagged control for the exact findings — compromise reduces the score; expected/risk-surface do not, except a known CVE, which carries a small bounded penalty (high/critical → Review).
The same gate an agent runs before installing (POST /api/v1/trust/habitat-sim-3d-simulator/check). Click a policy:
Consume Habitat-Sim — High-Performance 3D Embodied AI Simulator programmatically. Authenticate with an API key or session — see Authorize an agent.
# Agents: CHECK BEFORE YOU INSTALL (no auth) — score, grade, level, capability manifest
curl https://ai-supply.store/api/v1/trust/habitat-sim-3d-simulator
# Gate against your org policy (returns { pass, violations })
curl -X POST https://ai-supply.store/api/v1/trust/habitat-sim-3d-simulator/check \
-H "Content-Type: application/json" \
-d '{"minGrade":"B","denyPermissions":["shell"],"denyUnknownEgress":true}'
# CLI
npx ai-supply add habitat-sim-3d-simulator
# REST (install → download)
curl -X POST https://ai-supply.store/api/v1/listings/habitat-sim-3d-simulator/install \
-H "Authorization: Bearer $AIM_KEY"
# MCP tool
install_listing({ "slug": "habitat-sim-3d-simulator" })OpenAPI spec →Curated mirror — latest upstream source. See the repository for tagged releases.