Add Dataset Usage

README.md

@@ -12,7 +12,7 @@ tags:
 ---
 
 # LAVN Dataset
-### Data Organization
+### Dataset Organization
 
 After downloading and unzipping the zip files, please reorganize the files in the following tructure:
 ```
@@ -96,6 +96,28 @@ where ```<SCENE_ID>``` matches exactly the original one in [Gibson](https://gith
 ```
 where ```[<LOC_X>, <LOC_Y>, <LOC_Z>]``` is the 3-axis location vector, ```<ORIENT>``` is the orientation only in simulation. ```[<COOR_X>, <COOR_Y>]``` are the image coordinates of landmarks. ```ACTION_NAME``` stores the action of the robot take from the current frame to the next frame.
 
+
+### Dataset Usage
+The visual navigation task can be formulated as various types of problems, including but not limited to:
+
+**1. Supervised Learning** by mapping visual observations (```RGBD```) to waypoints (image coordinates). A developer can
+design a vision network whose input (```X```) is ```RGBD``` and output (```Y```) is image coordinate, specified by ```img_path```, ```depth_path```
+and click point ```[<COOR_X>, <COOR_Y>]``` in the worker ```graph.json``` file in the dataset. The loss function can
+be designed to minimize the discrepancy between the predicted image coordinate (```Y_pred```) and the ground truth (```Y```), e.g.
+```loss = ||Y_pred − Y||```. Then ```Y_pred``` can be simply translated to a robot’s moving action, such as ```Y_pred``` in the center or
+top region of an image means moving forward while ```left/right``` regions represent turning left or right.
+
+
+**2. Map Representation Learning** in the latent space of a neural network. One can train this latent space to represent two
+observations’ proximity by contrastive learning. The objective is to learn a function ```h()``` that predicts the distance given two
+observations (```X1```) and (```X2```): ```dist = h(X1, X2)```. Note that ```dist()``` can be a cosine or distance-based function, depending on
+the design choice. The positive samples can be nodes (a node includes information at a timestep such as ```RGBD``` data and image
+coordinates) nearby while further nodes can be treated as negative samples. A landmark is a sparse and distinct object or scene
+in the dataset that facilitates a more structured and global connection between nodes, which further assists in navigation in
+more complex or longer trajectories.
+
+
+
 ### Long-Term Maintenance Plan
 We will conduct a long-term maintenance plan to ensure the accessability and quality for future research: