Update README.md



README.md

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 <!-- Provide a quick summary of the dataset. -->
 
-**SimData-NuScenes** is a large-scale synthetic dataset generated from high-fidelity simulation environments. It is designed to facilitate research in autonomous driving perception, specifically for 3D object detection and tracking.
+**SimData-NuScenes** is a large-scale synthetic dataset generated from high-fidelity simulation environments using **aiSim**. 
+
+By leveraging **aiSim's** advanced physics engine and deterministic sensor modeling, we ensure that every frame maintains **high-quality visual fidelity and physical accuracy**. This makes the dataset particularly effective for training and validating perception algorithms where precision is paramount.
 
 The dataset follows the **NuScenes format (v1.0-custom)** and covers diverse environments including highways, complex urban areas, and parking lots across different geographic styles (US, Europe, Japan).
 
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 - **Diversity**: Covers Highway, Urban, and Parking scenarios.
 - **Volume**: Approximately **18,000+ frames** per sensor (Camera/LiDAR).
 
+### Sensor Layout
+    
+<div align="center">
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/69367df980cb6886b08b3cc9/Uf1-Txyyx2tycRjwP-ZwJ.png" width="80%" />
+</div>
+
+### Overview
+6 annotated surround-view camera images and BEV ground truth with LiDAR point clouds.
+<div align="center">
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/69367df980cb6886b08b3cc9/4uB-JKa9_HikgdcZfi31y.jpeg" width="80%" />
+</div>
+
 ## Dataset Statistics (统计数据)
 
 The dataset metadata is organized as follows: