# Panda two-cube stack

Panda two-cube stack. Bounded operational-space feedback, simulated contact and native task success checks.

Record version: `1.0.0` · Hub commit: `d800c48cfd84f618a5c6ab84f8f7feec74ab0b56`

## Executable interface

```json
{
  "version": "1",
  "kind": "task",
  "abstraction_level": 2,
  "execution_domain": "simulation",
  "language": "python",
  "input_transport": "json_file_or_inline",
  "output_transport": "json_stdout",
  "output_selector": "outputs",
  "conventions": {
    "linear_unit": "m",
    "angular_unit": "rad",
    "time_unit": "s",
    "coordinate_frame": "right_handed_world_xyz; +z_up",
    "joint_order": "not_used",
    "quaternion_order": "not_used"
  },
  "input_schema": {
    "type": "object",
    "required": [
      "seed"
    ],
    "properties": {
      "seed": {
        "type": "integer",
        "minimum": 0,
        "maximum": 10000
      }
    },
    "additionalProperties": false
  },
  "output_schema": {
    "type": "object",
    "required": [
      "object_xyz_m",
      "target_xyz_m",
      "error_m",
      "steps",
      "environment_success"
    ],
    "properties": {
      "object_xyz_m": {
        "type": "array",
        "minItems": 3,
        "maxItems": 3,
        "items": {
          "type": "number",
          "minimum": -30,
          "maximum": 30
        },
        "x-unit": "m",
        "x-frame": "right_handed_world_xyz; +z_up"
      },
      "target_xyz_m": {
        "type": "array",
        "minItems": 3,
        "maxItems": 3,
        "items": {
          "type": "number",
          "minimum": -30,
          "maximum": 30
        },
        "x-unit": "m",
        "x-frame": "right_handed_world_xyz; +z_up"
      },
      "error_m": {
        "type": "number",
        "minimum": 0,
        "maximum": 50
      },
      "steps": {
        "type": "integer",
        "minimum": 1,
        "maximum": 800
      },
      "environment_success": {
        "type": "boolean"
      }
    },
    "additionalProperties": false
  },
  "preconditions": [
    "Use the exact recorded source, Linux Python 3.10 environment and pinned direct packages.",
    "No physical robot, network actuation or external robot credentials."
  ],
  "postconditions": [
    "All reported checks must be true and all output numbers finite.",
    "Success covers the declared goal and frozen cases, not arbitrary tasks or physical hardware."
  ],
  "failure_codes": [
    "invalid_input_or_environment",
    "execution_failed",
    "task_failed"
  ],
  "composition": {
    "depends_on": [],
    "automatic_frame_conversion": false,
    "automatic_hardware_execution": false
  }
}
```



## Exact environment

| Runtime | Robot | Controller | Observation | OS | Python | Evidence |
| --- | --- | --- | --- | --- | --- | --- |
| robosuite 1.5.2 | Panda | OSC_POSE | privileged_state | linux x86_64 | >=3.10,<3.11 | task_complete |

Privileged simulator state and declared goals; no perception or real sensor validation.

Compatibility status: **hub_verified**. An environment match does not establish task completion. Runtime verification: **task_complete**.

## Source and license

- Repository: https://github.com/ARISE-Initiative/robosuite
- Source commit: `824ac14cefcfb7ec125fe5eb2e0bad7364466154` (no tag)
- Original authors: Original robosuite contributors (preserve pinned LICENSE)
- License: [MIT](https://github.com/ARISE-Initiative/robosuite/blob/824ac14cefcfb7ec125fe5eb2e0bad7364466154/LICENSE)
- Source archive SHA256: `b0c9011b1a90e5faf3404e22694cb44eea012728f568dd9bccc8fde6063ab903`
- Upstream files: `LICENSE`, `robosuite/__init__.py`, `robosuite/environments/manipulation/lift.py`, `robosuite/controllers/parts/arm/osc.py`, `robosuite/environments/manipulation/stack.py`, `robosuite/environments/manipulation/pick_place.py`
- Upstream contribution rules: https://github.com/ARISE-Initiative/robosuite

## Find, inspect, prepare

```sh
python /PATH_TO_SKILL/scripts/rsh.py find "task" --runtime robosuite --runtime-version 1.5.2 --robot Panda --json
python /PATH_TO_SKILL/scripts/rsh.py inspect robosuite-panda-stack --json
python /PATH_TO_SKILL/scripts/rsh.py prepare robosuite-panda-stack --project ./experiment --expected-source-commit 824ac14cefcfb7ec125fe5eb2e0bad7364466154 --expected-record-version 1.0.0 --plan --json
```

Remove `--plan` to download the checksum-verified pinned source and create an isolated project environment. Preparation returns the remaining configuration. Dependency installation is an explicit `--install-deps` step; it can execute package build hooks. Robot simulation is a separate command returned by prepare, never run by find/inspect.

Direct package pins: `robosuite==1.5.2`, `mujoco==3.3.7`, `numpy==1.26.4`.

Direct runtime versions are pinned and measured. The receipt retains the complete environment freeze; prepare records the installed environment. System drivers are separate host requirements. Linux device dependencies may build evdev from source; an available C compiler and explicit dependency-install permission are required.

Hardware: Linux x86_64; CPU simulation; see retained receipt for the exact host environment.

Rendering: Headless. EGL libraries are required for MuJoCo imports; PushT uses SDL dummy video. No interactive display..

External API keys: none.

## Invocation contract

Entrypoint: `python run.py`.

```json
{
  "argv": [
    "{python}",
    "{recipe_dir}/run.py",
    "--source-dir",
    "{source_dir}",
    "--example"
  ],
  "inputs": {
    "seed": 0
  },
  "outputs": {
    "format": "single JSON object",
    "payload_selector": "outputs",
    "schema": {
      "type": "object",
      "required": [
        "object_xyz_m",
        "target_xyz_m",
        "error_m",
        "steps",
        "environment_success"
      ],
      "properties": {
        "object_xyz_m": {
          "type": "array",
          "minItems": 3,
          "maxItems": 3,
          "items": {
            "type": "number",
            "minimum": -30,
            "maximum": 30
          },
          "x-unit": "m",
          "x-frame": "right_handed_world_xyz; +z_up"
        },
        "target_xyz_m": {
          "type": "array",
          "minItems": 3,
          "maxItems": 3,
          "items": {
            "type": "number",
            "minimum": -30,
            "maximum": 30
          },
          "x-unit": "m",
          "x-frame": "right_handed_world_xyz; +z_up"
        },
        "error_m": {
          "type": "number",
          "minimum": 0,
          "maximum": 50
        },
        "steps": {
          "type": "integer",
          "minimum": 1,
          "maximum": 800
        },
        "environment_success": {
          "type": "boolean"
        }
      },
      "additionalProperties": false
    }
  }
}
```

Success: All declared goal and finite-state checks pass; exit 0 with task_complete. Native Stack or PickPlaceCan task success plus object/target distance <.08 m after release and retreat. No object teleportation after reset.

Timeout: 180 seconds. Terminate the adapter at the recorded timeout. No physical hardware is opened.

Failures: Invalid input or source checksum; Different pinned package version; Unavailable runtime/driver; Goal not reached within bounded steps.

## Actual evidence

All 3 frozen cases completed against this exact adapter and source.

Reviewer: Hub finite-case Lambda execution harness · 2026-10-20.

Commands/checks actually performed:

- python tools/verify_runtime_expansion.py --backend robosuite --source-cache SOURCE_CACHE --output OUTPUT

Submitted evidence and hub verification remain separate. A schema check, PR creation or merge does not establish task success or publication.

## Reusable fixes

Change the runtime expansion manifest/template, regenerate, and rerun all frozen cases. Preserve source/model/checkpoint licenses and distinguish simulation from hardware.

# Panda two-cube stack

Panda two-cube stack. Bounded operational-space feedback, simulated contact and native task success checks.

Native Stack or PickPlaceCan task success plus object/target distance <.08 m after release and retreat. No object teleportation after reset.

Source and model terms: MIT. The Hub wrapper is MIT. See the record for input JSON, exact environment, frozen execution receipts and preparation requirements.

