Update README.md

README.md

@@ -1,16 +1,16 @@
 size_categories:
-- 100M<n<1B
+- 50G<n<100G
 ---
 
 # 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.
+This dataset card aims to describe the PRTS Post-Training Data, which includes high-quality data for robotic manipulation tasks. The dataset encompasses both dual-arm and single-arm manipulation across a variety of tasks, including fine manipulation and long-range operations. It is curated in the **LeRobot format** to assist in the development and evaluation of robotic systems, particularly in tasks involving object manipulation 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.
+This dataset consists of robotic task data in the **LeRobot format**, covering various types of robotic manipulations such as dual-arm, single-arm, long-range, and fine manipulation tasks. It contains approximately 50GB of high-quality data generated from real-world robotic systems performing tasks in household, office, and industrial environments. The data includes detailed task frames including object handling, task coordination between two robotic arms, and complex manipulation actions.
 
 - **Curated by:** TeleEmbodied AI Team
 - **Funded by [optional]:** [More Information Needed]
@@ -29,31 +29,26 @@ This dataset consists of post-training data from robotic systems performing task
 ### 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
+- Dual-arm and single-arm manipulation tasks
+- Object pick-and-place and fine manipulation tasks
+- Long-range robotic operations and task planning
+- Evaluating robotic coordination, object handling, and task execution in real-world environments
 
-### Out-of-Scope Use
+## Dataset Structure
 
-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
+The dataset is curated in the **LeRobot format**. It contains data for multiple robotic tasks, each with the following key fields:
 
-## Dataset Structure
+- **`task_name`**: The name of the task (e.g., "Pick and Place Object").
+- **`task_id`**: A unique identifier for each task.
+- **`task_description`**: A brief description of the task.
+- **`frames`**: A collection of frames associated with the task. Each frame includes:
+  - **`t`**: Timestamp for the frame.
+  - **`pose`**: 6D pose of the robotic arms (for both left and right arms in dual-arm tasks).
+  - **`joints`**: Joint angles for the robotic arms (for both left and right arms in dual-arm tasks).
+  - **`gripper`**: Gripper state (open/close).
+
+Here’s an example of what the data structure looks like:
 
-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",