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Implementation:Facebookresearch Habitat lab Task dataset YAML config

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Domains Configuration_Management, Embodied_AI
Last Updated 2026-02-15 02:00 GMT

Overview

Concrete YAML configuration files for defining Habitat tasks and datasets, composed via Hydra defaults lists.

Description

Habitat provides pre-defined YAML configs for standard tasks and datasets:

  • Task YAMLs: `habitat-lab/habitat/config/habitat/task/pointnav.yaml`, `objectnav.yaml`, etc.
  • Dataset YAMLs: `habitat-lab/habitat/config/habitat/dataset/pointnav/gibson.yaml`, etc.

These are composed via Hydra defaults and define the full evaluation specification.

Usage

Reference task and dataset configs in your benchmark or training config. Use Hydra overrides to switch between tasks and datasets.

Code Reference

Source Location

  • Repository: habitat-lab
  • File: habitat-lab/habitat/config/habitat/task/pointnav.yaml, habitat-lab/habitat/config/habitat/dataset/pointnav/gibson.yaml

Signature

# pointnav.yaml (task definition)
type: Nav-v0
lab_sensors:
  pointgoal_with_gps_compass_sensor:
    type: PointGoalWithGPSCompassSensor
measurements:
  distance_to_goal:
    type: DistanceToGoal
  success:
    type: Success
    success_distance: 0.2
  spl:
    type: SPL
actions:
  stop:
    type: StopAction
  move_forward:
    type: MoveForwardAction
  turn_left:
    type: TurnLeftAction
  turn_right:
    type: TurnRightAction

Import

# Referenced via Hydra defaults in benchmark config
defaults:
  - habitat/task: pointnav
  - habitat/dataset: pointnav/gibson

I/O Contract

Inputs

Name Type Required Description
Task YAML file Yes Task definition with sensors, measures, actions
Dataset YAML file Yes Dataset path and type specification

Outputs

Name Type Description
Task config section DictConfig Task parameters merged into overall config
Dataset config section DictConfig Dataset parameters merged into overall config

Usage Examples

PointNav with Gibson

# benchmark_config.yaml
defaults:
  - habitat/task: pointnav
  - habitat/dataset: pointnav/gibson
  - _self_

habitat:
  dataset:
    split: val

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