---
license: cc-by-4.0
language:
- en
tags:
- robotics
- isaac-sim
- task-planning
pretty_name: SwiftPlan Isaac Sim Dataset
---

# SwiftPlan Isaac Sim Dataset

This dataset contains Isaac Sim observation images for frame-level high-level action selection in robotic task planning.

Each sample includes:

- an RGB observation image,
- a task instruction,
- a frame-level high-level action label,
- an action type,
- an optional target object.

The dataset is designed for execution-time high-level decision making, where a model selects the next high-level action from the current observation and task instruction.

## Splits

This dataset provides two fixed splits:

- `train`
- `test`

## Data Format

Each split folder contains images and a `metadata.jsonl` file.

Example:

```json
{
  "id": "swiftplan_isaac_000000",
  "file_name": "000000_capture_orange_20260418_205731_247523.png",
  "instruction": "prepare the fruits",
  "action_label": "pickup orange",
  "action_type": "pickup",
  "target_object": "orange",
  "split": "train"
}
```

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("Kuoskyler/swiftplan-isaac-sim")
print(dataset)
print(dataset["train"][0])
```

## USD file

The Isaac Sim USD scene file is also included in this dataset.

## Task

Given an RGB observation image and a task instruction, predict the next high-level action label.