Example Environments#

Isaac Lab Arena ships a catalog of ready-to-run example environments under isaaclab_arena_environments/. Each environment is a small composition of the building blocks introduced in Concept Overview — Scene, Embodiment, and Task — wrapped in an ExampleEnvironmentBase subclass and registered with the global EnvironmentRegistry.

The registered Task ID listed below is the value passed as the positional example_environment argument to scripts such as isaaclab_arena/evaluation/policy_runner.py, isaaclab_arena/scripts/imitation_learning/record_demos.py, and isaaclab_arena/scripts/imitation_learning/replay_demos.py.

The metadata below follows the same structure as the Key Specifications tables in the Imitation Learning and Reinforcement Learning workflow guides.

Pick & Place #

kitchen_pick_and_place#

Task ID: kitchen_pick_and_place

Class: KitchenPickAndPlaceEnvironment (isaaclab_arena_environments/kitchen_pick_and_place_environment.py)

Task Description: Pick an object off the kitchen counter top and place it inside a kitchen cabinet. Supports a single object via --object or a heterogeneous --object_set spawning a different object per environment.

Property	Value
Tags	Table-top manipulation
Skills	Reach, Grasp, Pick & place
Embodiment	`franka_ik` (default), configurable via `--embodiment`
Scene	`kitchen` background, counter top reference (anchor), cabinet destination
Objects	Configurable via `--object` / `--object_set` (e.g. `tomato_soup_can`, `cracker_box`)
Task Class	`PickAndPlaceTask`
Object Placement	Relations: `On(table_top)`, `AtPosition(x=0.4, y=0.0)`
CLI Args	`--object`, `--object_set`, `--embodiment`, `--teleop_device`

pick_and_place_maple_table#

Task ID: pick_and_place_maple_table

Class: PickAndPlaceMapleTableEnvironment (isaaclab_arena_environments/pick_and_place_maple_table_environment.py)

Task Description: Tabletop pick-and-place on the maple Robolab table; used as the introductory First Arena Environment walkthrough.

Property	Value
Tags	Table-top manipulation
Skills	Reach, Grasp, Pick & place
Embodiment	`droid_abs_joint_pos` (default), configurable via `--embodiment`
Scene	`maple_table_robolab` background, dome `light` (configurable HDR / intensity)
Objects	Pick: `rubiks_cube_hot3d_robolab` (default); Destination: `bowl_ycb_robolab` (default); plus optional `--additional_table_objects`
Task Class	`PickAndPlaceTask` (episode_length_s = 20)
Object Placement	Relations: `On(table)`, `PositionLimits(x=0.55..0.70, y=-0.4..-0.1)`
CLI Args	`--pick_up_object`, `--destination_location`, `--additional_table_objects`, `--embodiment`, `--teleop_device`, `--hdr`, `--light_intensity`

galileo_pick_and_place#

Task ID: galileo_pick_and_place

Class: GalileoPickAndPlaceEnvironment (isaaclab_arena_environments/galileo_pick_and_place_environment.py)

Task Description: Pick up an object in the Galileo lab environment and place it into a small bin on the shelf.

Property	Value
Tags	Table-top manipulation, lab scene
Skills	Reach, Grasp, Pick & place
Embodiment	`gr1_pink` (default), configurable via `--embodiment`
Scene	`galileo` lab background; bin lid (`small_bin_grid_01/lid`) used as destination reference
Objects	`power_drill` (default), configurable via `--object`
Task Class	`PickAndPlaceTask`
CLI Args	`--object`, `--embodiment`, `--teleop_device`

galileo_g1_locomanip_pick_and_place#

Task ID: galileo_g1_locomanip_pick_and_place

Class: GalileoG1LocomanipPickAndPlaceEnvironment (isaaclab_arena_environments/galileo_g1_locomanip_pick_and_place_environment.py)

Task Description: The G1 humanoid navigates the lab, squats, and picks an object off a shelf to place it into a bin on a table to its right. Featured in the G1 Loco-Manipulation Box Pick and Place Task workflow.

Property	Value
Tags	Room-scale loco-manipulation
Skills	Squat, Turn, Walk, Pick, Place
Embodiment	`g1_wbc_pink` (default; whole-body controller w/ navigation P-controller in Mimic)
Scene	`galileo_locomanip` background
Objects	Pick: `brown_box` (default); Destination: `blue_sorting_bin` (default)
Task Class	`LocomanipPickAndPlaceTask` (episode_length_s = 30, force / velocity success thresholds)
Interop	Isaac Lab Mimic (legacy `locomanip_pick_and_place_D0` datagen for the brown-box → blue-bin pair)
CLI Args	`--object`, `--destination`, `--embodiment`, `--teleop_device`, `--task_description`

Articulated Object Manipulation #

gr1_open_microwave#

Task ID: gr1_open_microwave

Class: Gr1OpenMicrowaveEnvironment (isaaclab_arena_environments/gr1_open_microwave_environment.py)

Task Description: The GR1T2 humanoid reaches with its upper body to open a microwave door. Featured in the GR1 Open Microwave Door Task workflow.

Property	Value
Tags	Table-top manipulation, articulated objects
Skills	Reach, Open door
Embodiment	`gr1_pink` (default) or `gr1_joint` via `--embodiment`
Scene	`kitchen` background, `microwave` placed on the packing table
Objects	`microwave` (articulated); optional `--object` placed in front of the microwave
Task Class	`OpenDoorTask` (openness_threshold = 0.8, reset_openness = 0.2, episode_length_s = 5)
CLI Args	`--object`, `--teleop_device`, `--embodiment`

gr1_turn_stand_mixer_knob#

Task ID: gr1_turn_stand_mixer_knob

Class: Gr1TurnStandMixerKnobEnvironment (isaaclab_arena_environments/gr1_turn_stand_mixer_knob_environment.py)

Task Description: GR1 humanoid turns the dial on a stand mixer to a target level.

Property	Value
Tags	Table-top manipulation, articulated objects
Skills	Reach, Grasp knob, Turn
Embodiment	`gr1_pink` (default) or `gr1_joint` via `--embodiment`
Scene	`kitchen` background, `stand_mixer` on the packing table
Objects	`stand_mixer` (articulated); optional `--object` placed in front
Task Class	`TurnKnobTask`
CLI Args	`--object`, `--target_level` (default 4), `--reset_level` (default -1), `--embodiment`, `--teleop_device`

press_button#

Task ID: press_button

Class: PressButtonEnvironment (isaaclab_arena_environments/press_button_environment.py)

Task Description: Press the button on a coffee machine.

Property	Value
Tags	Table-top manipulation, articulated objects
Skills	Reach, Press
Embodiment	`franka_ik` (default) via `--embodiment`
Scene	`packing_table` background, `coffee_machine` placed on top
Objects	`coffee_machine` (articulated)
Task Class	`PressButtonTask` (reset_pressedness = 0.8)
CLI Args	`--embodiment`, `--teleop_device`

Sorting #

tabletop_sort_cubes#

Task ID: tabletop_sort_cubes

Class: TableTopSortCubesEnvironment (isaaclab_arena_environments/sorting_environment.py)

Task Description: Sort two cubes into two color-matching containers on a table.

Property	Value
Tags	Table-top manipulation, multi-object
Skills	Pick, Place, Sort
Embodiment	`franka_ik` (only supported value)
Scene	`table` background (configurable), `light`
Objects	`--objects` (default `red_cube green_cube`); `--destinations` (default `red_container green_container`); exactly 2 of each required
Task Class	`SortMultiObjectTask` (custom success force_threshold = 0.1)
CLI Args	`--objects`, `--destinations`, `--background`, `--embodiment`, `--teleop_device`

Assembly #

peg_insert#

Task ID: peg_insert

Class: PegInsertEnvironment (isaaclab_arena_environments/tabletop_peginsert_environment.py)

Task Description: Assemble a peg into a hole on a tabletop.

Property	Value
Tags	Tabletop, contact-rich assembly
Skills	Reach, Grasp, Insert
Embodiment	`franka_ik` (default; assembly high-PD config) via `--embodiment`
Scene	`table` background (configurable), dome `light`
Objects	Pick: `peg` (default); Destination: `hole` (default)
Task Class	`AssemblyTask` (min_separation = 0.1, randomized x/y/yaw pose range)
CLI Args	`--object`, `--destination_object`, `--background`, `--embodiment`, `--teleop_device`

gear_mesh#

Task ID: gear_mesh

Class: GearMeshEnvironment (isaaclab_arena_environments/tabletop_gearmesh_environment.py)

Task Description: Pick a medium gear and mesh it onto a gear base, with small and large reference gears already mounted.

Property	Value
Tags	Tabletop, contact-rich assembly
Skills	Reach, Grasp, Mesh
Embodiment	`franka_ik` (default; assembly high-PD config) via `--embodiment`
Scene	`table` background (configurable), dome `light`
Objects	`gear_base`, `medium_gear` (held), `small_gear` and `large_gear` (auxiliary)
Task Class	`AssemblyTask` (held-fixed-and-auxiliary randomization, min_separation = 0.18)
CLI Args	`--background`, `--embodiment`, `--teleop_device`

tabletop_place_upright#

Task ID: tabletop_place_upright

Class: TableTopPlaceUprightEnvironment (isaaclab_arena_environments/tabletop_place_upright_environment.py)

Task Description: Pick a tipped-over mug on the table and place it upright.

Property	Value
Tags	Table-top manipulation, re-orientation
Skills	Reach, Grasp, Re-orient, Place
Embodiment	`agibot` (only supported value; `ArmMode.LEFT`)
Scene	`table` background (configurable), `ground_plane`, `light`
Objects	`mug` (default) via `--object`
Task Class	`PlaceUprightTask` (custom event `randomize_mug_positions`)
CLI Args	`--object`, `--background`, `--embodiment`, `--teleop_device`

Goal-Pose / Lift (RL)#

cube_goal_pose#

Task ID: cube_goal_pose

Class: CubeGoalPoseEnvironment (isaaclab_arena_environments/cube_goal_pose_environment.py)

Task Description: Reach a target 6-DoF pose with a cube (goal-conditioned manipulation).

Property	Value
Tags	Table-top manipulation, goal-conditioned
Skills	Reach, Grasp, Re-orient
Embodiment	`franka_ik` (default) via `--embodiment`
Scene	`table` background (configurable), `light`
Objects	`dex_cube` (default) via `--object`
Task Class	`GoalPoseTask` (target_z_range = [0.2, 1.0], target_orientation_xyzw = yaw 90°, tolerance = 0.2 rad)
CLI Args	`--object`, `--background`, `--embodiment`, `--teleop_device`

lift_object#

Task ID: lift_object

Class: LiftObjectEnvironment (isaaclab_arena_environments/lift_object_environment.py)

Task Description: Reinforcement-learning task in which the Franka Panda learns to grasp and lift an object to a commanded target position. Featured in the Franka Lift Object Task workflow.

Property	Value
Tags	Table-top manipulation, RL training
Skills	Reach, Grasp, Lift
Embodiment	`franka_joint_pos` (default; joint-position control yields better RL success than IK) via `--embodiment`
Scene	`table` background, `ground_plane`, `light`
Objects	`dex_cube` (default) via `--object`
Task Class	`LiftObjectTaskRL` (minimum_height_to_lift = 0.04, episode_length_s = 5)
Training Method	Reinforcement Learning (RSL-RL PPO; `rl_policy_cfg` = `base_rsl_rl_policy:RLPolicyCfg`)
CLI Args	`--object`, `--embodiment`, `--teleop_device`, `--rl_training_mode`

dexsuite_lift#

Task ID: dexsuite_lift

Class: DexsuiteLiftEnvironment (isaaclab_arena_environments/dexsuite_lift_environment.py)

Task Description: Evaluation wrapper around the Isaac Lab Isaac-Dexsuite-Kuka-Allegro-Lift-v0 MDP. The Kuka arm with an Allegro dexterous hand lifts a procedurally generated cuboid to a commanded target position. Featured in the Dexsuite Kuka Allegro Lift Task (Newton) workflow.

Property	Value
Tags	Dexterous manipulation, contact-rich, RL evaluation
Skills	Reach, Grasp, Lift (multi-finger)
Embodiment	`kuka_allegro` (fixed)
Scene	`procedural_table` background, `ground_plane`, `light`
Objects	`procedural_cube` (randomized initial pose with a wide `PoseRange`)
Task Class	`DexsuiteLiftTask` (object_pose command, position-only, resampled every 2–3 s)
Training Method	Pre-trained in Isaac Lab via `DexsuiteKukaAllegroPPORunnerCfg` (RSL-RL PPO)
Physics Backend	PhysX (default) or Newton (`--presets newton`)
CLI Args	(none environment-specific; uses common ``ArenaEnvBuilder`` flags)

Sandbox #

gr1_table_multi_object_no_collision#

Task ID: gr1_table_multi_object_no_collision

Class: GR1TableMultiObjectNoCollisionEnvironment (isaaclab_arena_environments/gr1_table_multi_object_no_collision_environment.py)

Task Description: Sandbox scene for testing the relation solver: an office table with multiple objects placed via On(table) plus the built-in no-overlap solver. No success task — useful for policy_runner smoke tests with zero_action or any policy.

Property	Value
Tags	Sandbox, multi-object placement
Skills	(none — no task)
Embodiment	`gr1_joint` (default) via `--embodiment`
Scene	`ground_plane`, `office_table`, `light`, table-top anchor
Objects	Default set: `cracker_box`, `sugar_box`, `tomato_soup_can`, `dex_cube`, `power_drill`, `red_container` (override via `--objects`)
Task Class	`NoTask` (optional time-out termination via `--episode_length_s`)
CLI Args	`--objects`, `--embodiment`, `--teleop_device`, `--episode_length_s`

Sequential / Composite Tasks #

put_item_in_fridge_and_close_door#

Task ID: put_item_in_fridge_and_close_door

Class: GR1PutAndCloseDoorEnvironment (isaaclab_arena_environments/gr1_put_and_close_door_environment.py)

Task Description: GR1 humanoid sequentially picks an object, places it on the refrigerator shelf, then closes the refrigerator door. Featured in the GR1 Sequential Pick & Place and Close Door Task workflow.

Property	Value
Tags	Sequential manipulation, articulated objects
Skills	Pick, Place, Close door
Embodiment	`gr1_pink` (default) via `--embodiment`
Scene	`lightwheel_robocasa_kitchen` background (`--kitchen_style` selectable), `light`, kitchen counter anchor
Objects	Pick: `ranch_dressing_hope_robolab` (default), or `--object_set` for heterogeneous spawning; Destination: refrigerator shelf reference; Container: `refrigerator` (articulated)
Task Class	`PutAndCloseDoorTask` (sequential: `PickAndPlaceTask` → `CloseDoorTask`, episode_length_s = 10)
Interop	Isaac Lab Mimic (`put_and_close_door_task_D0` datagen)
CLI Args	`--object`, `--object_set`, `--kitchen_style`, `--embodiment`, `--teleop_device`

franka_put_and_close_door#

Task ID: franka_put_and_close_door

Class: FrankaPutAndCloseDoorEnvironment (isaaclab_arena_environments/franka_put_and_close_door_environment.py)

Task Description: Sequential pick-and-place of an object into a microwave, followed by closing the microwave door.

Property	Value
Tags	Sequential manipulation, articulated objects
Skills	Pick, Place, Close door
Embodiment	`franka_ik` (default) via `--embodiment`
Scene	`kitchen` background, `microwave` (articulated, starts open)
Objects	Pick: `dex_cube` (default) via `--object`; Container: `microwave`
Task Class	`FrankaPutAndCloseDoorTask` (sequential: `PickAndPlaceTask` → `CloseDoorTask`)
CLI Args	`--object`, `--embodiment`, `--teleop_device`