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diff --git a/README.md b/README.md
@@ -1,178 +1,53 @@
 # PySocialForce
 
-master: [![Build Status](https://travis-ci.com/yuxiang-gao/PySocialForce.svg?branch=master)](https://travis-ci.com/yuxiang-gao/PySocialForce)
-dev: [![Build Status](https://travis-ci.com/yuxiang-gao/PySocialForce.svg?branch=dev)](https://travis-ci.com/yuxiang-gao/PySocialForce)
-
-A Python Implementation of the Extended Social Force Model for Pedestrian Dynamics
-
-## Table of Contents
-
-- [PySocialForce](#pysocialforce)
-  - [Table of Contents](#table-of-contents)
-  - [About The Project](#about-the-project)
-    - [Roadmap](#roadmap)
-  - [Installation](#installation)
-  - [Usage](#usage)
-  - [Configuration](#configuration)
-  - [Examples](#examples)
-    - [Ped-ped Scenarios](#ped-ped-scenarios)
-    - [Environmental obstacles](#environmental-obstacles)
-    - [Groups](#groups)
-  - [Contributing to this project](#contributing-to-this-project)
-  - [License](#license)
-  - [Acknowledgements](#acknowledgements)
-  - [References](#references)
-
-## About The Project
-
-This project is a NumPy implementation of the **Extended Social Force Model** [[2]](#2).
-It extends the vanilla social force model [[1]](#1) to simulate the walking behaviour of pedestrian social groups.
-
-### Roadmap
-
-- [x] Simulation of indiviual pedestrians
-- [x] Social groups simulation
-- [ ] Inter-group interactions
-- [x] Environmental obstacles
-- [ ] Better environment representation
-- [x] Easy configuration with toml file
-- [x] Visualization of indiviuals and groups
-- [ ] Visualization of forces/potentials
+[](https://github.com/Bonifatius94/PySocialForce/actions/workflows/ci.yml/badge.svg)
 
-## Installation
-
-1. Clone the PySocialForce repo
-
-    ```sh
-    git clone https://github.com/yuxiang-gao/PySocialForce.git
-    ```
-
-2. (optional) Create a python virtual environment and activate it
-3. Install the pip package
-
-    ```sh
-        # Option 1: install from PyPI
-        pip install 'pysocialforce[test,plot]'
-
-        # Option 2:  install from source
-        pip install -e '.[test,plot]'
+## About
+This project is a Python implementation of the **Extended Social Force Model** [[2]](#2).
+It extends the vanilla social force model [[1]](#1) to simulate the walking behaviour
+of pedestrians with social group interactions.
 
-        # run linting and tests
-        pylint pysocialforce
-        pytest tests/*.py
-    ```
+The pedestrian states and other simulated entities are represented by NumPy arrays.
+Performance-critical implementations of forces use Numba for significant speed-ups.
 
-## Usage
+## Installation
 
-Basic usage:
+Clone the source code.
 
-```python
-import pysocialforce as psf
-# initiate simulator
-sim = psf.Simulator(
-        initial_state, groups=groups, obstacles=obstacles
-    )
-# do 50 updates
-sim.step(n=50)
+```sh
+git clone https://github.com/Bonifatius94/PySocialForce.git
 ```
 
-To generate an animation of the simulation, use the `SceneVisualizer` context:
-
-```python
-with psf.plot.SceneVisualizer(simulator, "output_image") as sv:
-    sv.animate()
-```
-For more examples, please refer to the [examples folder](examples).
-
-## Configuration
-You can configure the parameters by passing in a [toml](https://github.com/toml-lang/toml) file to the simulator:
-```Python
-sim = psf.Simulator(
-        initial_state, groups=groups, obstacles=obstacles, config_file="user_config.toml"
-    )
-```
+Install the pysocialforce package and its dependencies using pip + setup.py.
 
-By default the simulator loads the configurations at [pysocialforce/utils/default.toml](pysocialforce/utils/default.toml).
-An example of the user config and the explanation of the parameters is provided at [examples/example.toml](examples/example.toml).
-Each force has a parameter named `factor`, which is the scale factor for that force. For specific parameters for each force, refer to the comments in the example below:
-```Toml
-...
-[desired_force]
-factor = 1.0
-# The relaxation distance of the goal
-goal_threshold = 0.2
-# How long the relaxation process would take
-relaxation_time = 0.5
-
-[social_force]
-factor = 5.1
-# relative importance of position vs velocity vector
-lambda_importance = 2.0
-# define speed interaction
-gamma = 0.35
-n = 2
-# define angular interaction
-n_prime = 3
-
-[obstacle_force]
-factor = 10.0
-# the standard deviation of obstacle force
-sigma = 0.2
-# threshold to trigger this force
-threshold = 3.0
-
-[group_coherence_force]
-factor = 3.0
-
-[group_repulsive_force]
-factor = 1.0
-# threshold to trigger this force
-threshold = 0.55
-
-[group_gaze_force]
-factor = 4.0
-# fielf of view
-fov_phi = 90.0
+```sh
+pip install -e .
 ```
 
-## Examples
+For development, run the automated tests and lint the coding style.
 
-### Ped-ped Scenarios
-
-| ![crossing](images/crossing.png)          | ![narrow](images/narrow_crossing.png) |
-| ----------------------------------------- | ------------------------------------- |
-| ![opposing](image/../images/opposing.png) | ![2opposing](images/2opposing.png)    |
-
-### Environmental obstacles
-
-| ![sperator](images/separator.gif)                                                                             | ![gate](images/gate.gif)                                                                                       |
-| ------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------- |
-| Emergent lane formation with Emergent lane formation with 30 pedestrians: ![walkway30](images/walkway_30.gif) | Emergent lane formation with Emergent lane formation with 60 pedestrians:  ![walkway60](images/walkway_60.gif) |
-
-### Groups
-
-![group crossing](images/group_crossing.gif)
+```sh
+pylint pysocialforce
+pytest tests
+```
 
-## Contributing to this project
-Thanks for your interest in contributing! PySocialForce is a open-source project and we welcome contributions of any kind.
-If you find a bug or have a feature request, feel free to contact us using [Github issues](https://github.com/yuxiang-gao/PySocialForce/issues). If you are reporting a bug, please try to include a minimal example to recreate it. If you are requesting a feature, please also give some possible use cases to justify the request.
-If you want to help with development, you can work on a fork of the project and start a pull request. Please document your code and make sure that you have added the necessary tests and examples. Please also adhere to [semantic versioning](https://semver.org).
+## Usage
+See the usage examples in the [examples](./examples/) folder.
 
 ## License
-
-Distributed under the MIT License. See `LICENSE` for more information.
-
-## Acknowledgements
-
-- This project is based on [svenkreiss](https://github.com/svenkreiss)'s implementation of the vanilla social force model.
-- The implementation of forces drew inspiration from the [pedsim_ros][pedsim_ros] package.
+This project is available under the MIT License.
 
 ## References
 
-<a id="1">[1]</a> Helbing, D., & Molnár, P. (1995). Social force model for pedestrian dynamics. Physical Review E, 51(5), 4282–4286. <https://doi.org/10.1103/PhysRevE.51.4282>
+<a id="1">[1]</a> Helbing, D., & Molnár, P. (1995). Social force model
+for pedestrian dynamics. Physical Review E, 51(5), 4282–4286.
+<https://doi.org/10.1103/PhysRevE.51.4282>
 
-<a id="2">[2]</a> Moussaïd, M., Perozo, N., Garnier, S., Helbing, D., & Theraulaz, G. (2010). The walking behaviour of pedestrian social groups and its impact on crowd dynamics. PLoS ONE, 5(4), 1–7. <https://doi.org/10.1371/journal.pone.0010047>
+<a id="2">[2]</a> Moussaïd, M., Perozo, N., Garnier, S., Helbing, D., & Theraulaz, G. (2010).
+The walking behaviour of pedestrian social groups and its impact on crowd dynamics.
+PLoS ONE, 5(4), 1–7. <https://doi.org/10.1371/journal.pone.0010047>
 
-[socialforce]: https://github.com/svenkreiss/socialforce
+<a id="3">[3]</a> Sven Kreiss's original Social Force implementation
+on [GitHub](https://github.com/svenkreiss/socialforce)
 
-[pedsim_ros]: https://github.com/srl-freiburg/pedsim_ros
+<a id="4">[4]</a> pedsim_ros implementation on [GitHub](https://github.com/srl-freiburg/pedsim_ros)
diff --git a/images/2opposing.png b/images/2opposing.png
diff --git a/images/crossing.png b/images/crossing.png
diff --git a/images/exmaple.gif b/images/exmaple.gif
diff --git a/images/gate.gif b/images/gate.gif
diff --git a/images/group_crossing.gif b/images/group_crossing.gif
diff --git a/images/narrow_crossing.png b/images/narrow_crossing.png
diff --git a/images/opposing.png b/images/opposing.png
diff --git a/images/paper-corridor.png b/images/paper-corridor.png
diff --git a/images/paper-example.png b/images/paper-example.png
diff --git a/images/separator.gif b/images/separator.gif
diff --git a/images/walkway_30.gif b/images/walkway_30.gif
diff --git a/images/walkway_60.gif b/images/walkway_60.gif
diff --git a/setup.py b/setup.py
@@ -30,23 +30,23 @@ def parse_requirements(filename):
     description="Numpy implementation of the Extended Social Force model.",
     long_description=README,
     long_description_content_type="text/markdown",
-    author="Yuxiang Gao",
-    author_email="[email protected]",
-    url="https://github.com/yuxiang-gao/PySocialForce",
+    author="Marco Tröster",
+    author_email="[email protected]",
+    url="https://github.com/Bonifatius94/PySocialForce",
     install_requires=parse_requirements("requirements.txt"),
-    extras_require={
-        "dev": ["black", "jupyter"],
-        "test": ["pylint", "pytest",],
-        "plot": ["matplotlib",],
-    },
-    classifiers=[
-        "Development Status :: 4 - Beta",
-        "Intended Audience :: Developers",
-        "Natural Language :: English",
-        "License :: OSI Approved :: MIT License",
-        "Operating System :: OS Independent",
-        "Programming Language :: Python",
-        "Programming Language :: Python :: 3.7",
-        "Programming Language :: Python :: 3.8",
-    ],
+    # extras_require={
+    #     "dev": ["black", "jupyter"],
+    #     "test": ["pylint", "pytest",],
+    #     "plot": ["matplotlib",],
+    # },
+    # classifiers=[
+    #     "Development Status :: 4 - Beta",
+    #     "Intended Audience :: Developers",
+    #     "Natural Language :: English",
+    #     "License :: OSI Approved :: MIT License",
+    #     "Operating System :: OS Independent",
+    #     "Programming Language :: Python",
+    #     "Programming Language :: Python :: 3.7",
+    #     "Programming Language :: Python :: 3.8",
+    # ],
 )