habitat-gs-control

Apps & Automation

Interactively pilot a robot in habitat-gs 3D Gaussian Splatting indoor scenes via MCP tools — load a scene, move, observe with RGB/depth, run autonomous nav loops, and export video. Use for hands-on control of a live sim session, NOT for training or evaluating a navigation policy (use the habitat-gs-train skill for that).

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habitat-gs-control

Control a robot navigating through photo-realistic 3D indoor environments. You have MCP tools for scene loading, movement, observation, and autonomous navigation.

IMPORTANT: Always use MCP tools (hab_init, hab_look, hab_forward, etc.) directly. Do NOT use exec or shell commands — the MCP tools are the only supported interface.

What you can do

Observe: hab_look (current view), hab_panorama (4-direction scan with depth), hab_depth_analyze (obstacle distances)
Move: hab_forward (walk forward), hab_turn (rotate left/right)
Navigate: hab_navigate (auto-walk to coordinates), hab_find_path (plan route), hab_topdown (overhead map)
Long tasks: hab_nav_loop_start (launch autonomous navigation sub-agent), hab_nav_loop_status (check progress), hab_nav_loop_stop
Session: hab_init (load scene), hab_close (end session), hab_export_video (replay video)

How to use

Always init first: call hab_init to load a scene before anything else.
Look before you move: use hab_look or hab_panorama to see the environment, then decide where to go.
For simple tasks (move forward, look around): use tools directly.
For complex navigation (find an object, reach a goal, follow instructions): use hab_nav_loop_start with a goal description. It launches an autonomous sub-agent that navigates independently. Check progress with hab_nav_loop_status only when asked.
Export video when the task is done: hab_export_video encodes all captured frames into an mp4.

Navigation modes

The scene may run in two modes (auto-detected):

	navmesh	mapless
Map tools (`hab_navigate`, `hab_find_path`, `hab_topdown`)	available	not available
Coordinates visible	yes	no — only `euclidean_distance_to_goal` and `goal_direction_deg`
How to navigate	use `hab_navigate` for efficient multi-step movement	use `hab_forward`/`hab_turn` with depth checks

Task types for nav_loop

Type	What it does
`pointnav`	Navigate to a target coordinate
`objectnav`	Find a specific object in the scene
`imagenav`	Find the viewpoint matching a reference image
`eqa`	Explore and answer a question about the environment
`instruction_following`	Follow step-by-step natural language instructions

Examples:

PointNav: hab_nav_loop_start(task_type="pointnav", goal_x=1.0, goal_y=0.2, goal_z=-3.0)
ObjectNav: hab_nav_loop_start(task_type="objectnav", goal_description="find the kitchen door")
EQA: hab_nav_loop_start(task_type="eqa", goal_description="Is there a microwave in this scene?")
ImageNav: requires reference_image — see below

ImageNav workflow

ImageNav needs a reference image to match. You must capture it first:

Call hab_look — note the image path from the result (e.g. "/path/to/session_step000001_color_sensor.png")
Move the robot away: hab_forward, hab_turn
Start imagenav with the saved path: hab_nav_loop_start(task_type="imagenav", goal_description="match the reference view", reference_image="/path/to/session_step000001_color_sensor.png")

If you skip reference_image, the sub-agent will not know what view to look for.

Sending results to users

Use the media parameter in the message tool to send images or videos:

message(action="send", message="Here is the navigation replay", media="/path/to/video.mp4", filename="replay.mp4")

Do NOT paste file paths as plain text — always use the media parameter.

Troubleshooting

Problem	Solution
`Connection refused`	Bridge is not running — ask the user to start it
`Unknown session_id`	Session expired — call `hab_init` again
`ESP_CHECK failed`	Scene failed to load — try a different scene