diff --git a/README.md b/README.md
index 3fbc4c0..420f653 100644
--- a/README.md
+++ b/README.md
@@ -1,18 +1,21 @@
 # Multi-Purpose MPC
 
-## Table of contents 
+1. [Introduction](##Introduction)
+2. [Implementation Details](##ImplementationDetails)
+   1. [MPC](#MPC)
+3. [How-To](##How-To)
+4. [Limitations and Outlook](##Limitations and Outlook)
+4. [Contributors](#Contributors)
 
-1. [Introduction](#introduction)
-3. [Components](#components)
-   1. [MPC](#mpc)
-4. [How-To](#how_to)
-5. [Contributors](#contributors)
-
-# Introduction
+## Introduction
 
 In this repository you find an implementation of a multi-purpose Model Predictive Controller. The controller was implemented as a contribution to the [Automatic Control Project Course (EL2425)](https://www.kth.se/student/kurser/kurs/EL2425) at KTH Royal Institute of Technology, Stockholm. 
-The developed algorithm was tested on a 1:10 RC car provided by KTH Smart Mobility Lab. The test scenarios comprised the following three tasks:
+The developed algorithm was tested on a 1:10 RC car provided by [KTH Smart Mobility Lab](https://www.kth.se/dcs/research/control-of-transport/smart-mobility-lab/smart-mobility-lab-1.441539). The test scenarios comprised the following three tasks:
 
 1. Reference Path Tracking
 2. Time-Optimal Driving
 3. Obstacle Avoidance
+
+The controller is implemented in a way that enables its application to all three tasks by merely tuning the weight matrices of the underlying optimization problem. The illustration below shows the obstacle avoidance task in simulation.
+
+The rest of this readme is structured as follows. In [Section 2](##Components) we will present an overview of the entire system and discuss all fundamental components of the implementation in detail. In [Section 3](##How-To) we will provide guidelines for using the implementation in simulation and practice. [Section 4](##Limitations) will be dedicated to analyzing limitations of the current version of the controller and outline potential extensions of the implementation.