Create README.md

README.md

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+# Dataset Card for PRTS Post-Training Data
+
+This dataset card aims to describe the PRTS Post-Training Data, which includes various dual-arm robotic tasks across multiple domains such as household, office, and industrial environments. It is designed to facilitate research and development in robotic manipulation, task planning, and human-robot collaboration.
+
+## Dataset Details
+
+### Dataset Description
+
+This dataset consists of post-training data from robotic systems performing tasks across different scenarios, such as household, office, and industrial tasks. The dataset includes detailed task frames that encompass dual-arm manipulation, object handling, and collaborative operations. The data includes task names, timestamps, poses, joint angles, and gripper states, which can be used for training and evaluating robotic systems in various real-world environments.
+
+- **Curated by:** TeleEmbodied AI Team
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Language(s) (NLP):** Not applicable (robotics tasks)
+- **License:** MIT License
+
+### Dataset Sources [optional]
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+### Direct Use
+
+This dataset is intended for the following use cases:
+- Dual-arm robotic manipulation tasks
+- Object pick-and-place tasks
+- Collaborative tasks between two robotic arms
+- Testing robotic task planning and execution in different environments
+
+### Out-of-Scope Use
+
+This dataset is not suitable for:
+- Tasks unrelated to dual-arm robotic manipulation
+- Tasks involving single-arm operations
+- Use cases that require high-level cognitive or decision-making tasks beyond basic manipulation
+
+## Dataset Structure
+
+This dataset consists of over 30 tasks, each with the following fields:
+- `task_name`: Name of the task (e.g., "Pick and Place Object").
+- `task_id`: Unique identifier for each task.
+- `task_description`: A brief description of what the task involves.
+- `frames`: A list of frames associated with the task, where each frame contains:
+  - `t`: Timestamp for the frame.
+  - `pose`: 6D pose of the robotic arms.
+  - `joints`: Joint angles for the robotic arms.
+  - `gripper`: Gripper state (open/close).
+
+Example:
+```json
+{
+    "task_name": "Pick and Place Object",
+    "task_id": "001",
+    "task_description": "Pick up a cup and place it on the table",
+    "frames": [
+        {
+            "t": 0.0,
+            "pose": [0.5, 0.5, 0.2, 0, 0, 0, 1],
+            "joints": [0.3, -0.5, 0.8, 0.1, -0.2, 0.9, 0.2, -0.4],
+            "gripper": [1, 0]
+        }
+    ]
+}