Update README.md

Update README.md to add detailed task descriptions

README.md

@@ -19,6 +19,28 @@ This dataset was created using [LeRobot](https://github.com/huggingface/lerobot)
 - **Paper:** [More Information Needed]
 - **License:** apache-2.0
 
+- **Task Objective:** Place the RealSense D-405 camera into the mounting case and secure the lid.
+- **Operational Objects:** A RealSense D-405 camera along with its original complete packaging (Purchase link: [【淘宝】退货运费险 https://e.tb.cn/h.60YgeNsj0ZmKJD1?tk=VwPYeJGcavx tG-#22>lD 「英特尔RealSense D405近距离7~50cm高精度毫米深度相机实感摄像头」点击链接直接打开 或者 淘宝搜索直接打开])
+- **Operation Duration:** Each operation takes approximately 20 to 40 seconds.  
+- **Recording Frequency:** 30 Hz.  
+- **Robot Type:** 7-DOF dual-arm G1 robot.  
+- **End Effector:** Three-fingered dexterous hands.  
+- **Dual-Arm Operation:** Yes.  
+- **Image Resolution:** 640x480.  
+- **Camera Positions:** Wrist-mounted (monocular camera) + head-mounted (binocular cameras).  
+- **Data Content:**  
+ • Robot's current state.  
+ • Robot's next action.  
+ • Current camera view images.  
+- **Robot Initial Posture:** The first robot state in each dataset entry.  
+- **Object Placement:** Position the camera case at the midpoint between the robot's arms in their initial state (arms vertical), 30cm away from the inner edge of the table's wall (robot-facing side). Place the camera on the right side of the case, and position the lid on the left side of the case.  
+- **Camera View:** Follow the guidelines in **Part 5** of [AVP Teleoperation Documentation](https://github.com/unitreerobotics/avp_teleoperate).  
+
+- **Important Notes:**  
+1. Due to the inability to precisely describe spatial positions, adjust the scene to closely match the first frame of the dataset after installing the hardware as specified in **Part 5** of [AVP Teleoperation Documentation](https://github.com/unitreerobotics/avp_teleoperate).  
+2. Data collection is not completed in a single session, and variations between data entries exist. Ensure these variations are accounted for during model training.  
+
+
 ## Dataset Structure
 
 [meta/info.json](meta/info.json):