diff --git a/docs/howto/how_to_understand_architecture_and_workflow.md b/docs/howto/how_to_understand_architecture_and_workflow.md
index 907f493e83b94974d3eeef89f0e76036c150ccd2..cd2f9830fe48623476cdd72ea53c7b4a4f5e3671 100644
--- a/docs/howto/how_to_understand_architecture_and_workflow.md
+++ b/docs/howto/how_to_understand_architecture_and_workflow.md
@@ -101,7 +101,7 @@ output observed Obstacles info. In the latest version of the codes, different ha
 different parallel locations, which consists of *Lidar, Radar, Traffic lights and GPS*.
 
 1. Lidar:
-   - Hadmap: get transformation matrix convert point world coordinates to local coordinates and build map polygons
+   - Hdmap: get transformation matrix convert point world coordinates to local coordinates and build map polygons
    - ROI filter: get ROI and perform Kalman Filter on input data
    - Segmentation: A U-Net based \(a lot of variants\) caffemodel will be loaded and perform forward computation based on data from Hdmap and ROI filtering results
    - Object Building: Lidar return points \(x, y, z\). Hence you need to group them into "Obstacles" \(vector or set\)