diff --git a/README.md b/README.md
index 0e992cc..58c727d 100644
--- a/README.md
+++ b/README.md
@@ -18,13 +18,13 @@
   <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
   <a href="https://github.com/uos/rmcl/issues">Issues</a>
   <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
-  <a href="https://github.com/aock/rmcl_example">Examples</a>
+  <a href="https://github.com/amock/rmcl_example">Examples</a>
   <br />
 </div>
 
 <br/>
 
-This repository contains algorithms designed for map-based robot localization, specifically when dealing with maps composed of triangle meshes or complete scene graphs. These maps may be provided by architects who have designed the building in which the robot operates, or they can be autonomously generated by the robot through Simultaneous Localization and Mapping (SLAM) methods. It's crucial to note that map-based localization differs from SLAM; it focuses on estimating the robot's pose within a potentially large map, whether the initial pose is roughly known (tracking) or entirely unknown from the start aka kidnapped robot problem. Map-based localization is essential for precisely planning the robot's missions in a given map.
+This repository contains algorithms designed for map-based robot localization, specifically when dealing with maps composed of triangle meshes or complete scene graphs. These maps may be provided by architects who have designed the building in which the robot operates, or they can be autonomously generated by the robot through Simultaneous Localization and Mapping (SLAM) methods. It's crucial to note that map-based localization differs from SLAM; it focuses on estimating the robot's pose within a potentially large map, whether the initial pose is roughly known (tracking) or entirely unknown from the start aka kidnapped robot problem. Map-based localization is essential for precisely planning the robot's missions on a given map.
 
 ## MICP-L
 
@@ -39,7 +39,7 @@ An approach to directly register range sensor data to a mesh in order to localiz
 | <a href="http://www.youtube.com/watch?v=5pubwlbrpro" target="_blank" ><img src="https://i.ytimg.com/vi/5pubwlbrpro/maxresdefault.jpg" alt="MICP-L Hilti Video" width="100%" style="max-width: 500px" height="auto" /></a> | <a href="http://www.youtube.com/watch?v=8j6ZtYPnFzw" target="_blank" ><img src="https://i.ytimg.com/vi/8j6ZtYPnFzw/maxresdefault.jpg" alt="MICP-L MulRan Video" width="100%" style="max-width: 500px" height="auto" /></a> |
 
 Requirements:
-- At least one range sensor equipped and running
+- At least one range sensor is equipped and running
 - Triangle mesh as map
 - Prior odometry estimation of the robot given as TF
 
@@ -294,7 +294,7 @@ Clone this repository into your ROS workspace and build it.
 
 ## Examples
 
-To learn how to use RMCL ROS nodes in your project, visit https://github.com/aock/rmcl_example.
+To learn how to use RMCL ROS nodes in your project, visit https://github.com/amock/rmcl_example.
 
 To learn how to use RMCL library in your Node: `src/nodes/examples`.