Merge pull request #2 from aayush-fadia/thermal-perception

Initial thermal-perception wiki entry Aayush

Author: p-amyjiang

_data/navigation.yml

@@ -139,6 +139,8 @@ wiki:
         url: /wiki/sensing/azure-block-detection/
       - title: DWM1001 UltraWideband Positioning System
         url: /wiki/sensing/ultrawideband-beacon-positioning.md
+      - title: Perception via Thermal Imaging
+        url: /wiki/sensing/thermal-perception/
   - title: Controls & Actuation
     url: /wiki/actuation/
     children:

wiki/sensing/thermal-perception.md

@@ -2,14 +2,25 @@
 # Jekyll 'Front Matter' goes here. Most are set by default, and should NOT be
 # overwritten except in special circumstances. 
 # You should set the date the article was last updated like this:
-date: 2020-05-11 # YYYY-MM-DD
+date: 2025-04-29 # YYYY-MM-DD
 # This will be displayed at the bottom of the article
 # You should set the article's title:
-title: Thermal Perception
+title: Perception via Thermal Imaging
 # The 'title' is automatically displayed at the top of the page
 # and used in other parts of the site.
 ---
-## TODO: Description
+
+In this article, we discuss strategies to implement key steps in a robotic perception pipeline using thermal cameras.
+Specifically, we discuss the conditions under which a thermal camera provides more utility than an RGB camera, followed
+by implementation details to perform camera calibration, dense depth estimation and odometry using thermal cameras.
+
+## Why Thermal Cameras?
+
+Thermal cameras are useful in key situations where normal RGB cameras fail - notably, in perceptual degradation like
+smoke and darkness.
+Furthermore, unlike LiDAR and RADAR, thermal cameras do not emit any detectable radiation.
+If your robot is expected to operate in darkness and smoke-filled areas, thermal cameras are a means for your robot to
+perceive the environment in nearly the same way as visual cameras would in ideal conditions.
 
 ## Why Depth is Hard in Thermal