Updated pypi readme

WHaoZhai · Jun 16, 2022 · ed11ee1 · ed11ee1
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diff --git a/pypi_description.md b/pypi_description.md
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 [Simple](https://en.wikipedia.org/wiki/KISS_principle) OpenAI [Gym environment](https://gym.openai.com/envs/#classic_control) based on [PyBullet](https://github.com/bulletphysics/bullet3) for multi-agent reinforcement learning with quadrotors 
 
-<img src="https://github.com/utiasDSL/gym-pybullet-drones/blob/master/files/readme_images/helix.gif" alt="formation flight" width="350"> <img src="https://github.com/utiasDSL/gym-pybullet-drones/blob/master/files/readme_images/helix.png" alt="control info" width="450">
-
-- The default `DroneModel.CF2X` dynamics are based on [Bitcraze's Crazyflie 2.x nano-quadrotor](https://www.bitcraze.io/documentation/hardware/crazyflie_2_1/crazyflie_2_1-datasheet.pdf)
-
-## Overview
-
-|                                   | `gym-pybullet-drones` | [AirSim](https://github.com/microsoft/AirSim) | [Flightmare](https://github.com/uzh-rpg/flightmare) |
-|---------------------------------: | :-------------------: | :-------------------------------------------: | :-------------------------------------------------: |
-|                         *Physics* | PyBullet              | FastPhysicsEngine/PhysX                       | *Ad hoc*/Gazebo                                     |
-|                       *Rendering* | PyBullet              | Unreal Engine 4                               | Unity                                               |
-|                        *Language* | Python                | C++/C#                                        | C++/Python                                          |  
-|           *RGB/Depth/Segm. views* | **Yes**               | **Yes**                                       | **Yes**                                             |
-|             *Multi-agent control* | **Yes**               | **Yes**                                       | **Yes**                                             |
-|                   *ROS interface* | ROS2/Python           | ROS/C++                                       | ROS/C++                                             |
-|            *Hardware-In-The-Loop* | No                    | **Yes**                                       | No                                                  |
-|         *Fully steppable physics* | **Yes**               | No                                            | **Yes**                                             |
-|             *Aerodynamic effects* | Drag, downwash, ground| Drag                                          | Drag                                                |
-|          *OpenAI [`Gym`](https://github.com/openai/gym/blob/master/gym/core.py) interface* | **Yes** | **[Yes](https://github.com/microsoft/AirSim/pull/3215)** | **Yes**                                             |
-| *RLlib [`MultiAgentEnv`](https://github.com/ray-project/ray/blob/master/rllib/env/multi_agent_env.py) interface* | **Yes** | No | No                           |
-
-
-## Citation
-If you wish, please cite our work [(link)](https://arxiv.org/abs/2103.02142) as
-```
-@INPROCEEDINGS{panerati2021learning,
-      title={Learning to Fly---a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control}, 
-      author={Jacopo Panerati and Hehui Zheng and SiQi Zhou and James Xu and Amanda Prorok and Angela P. Schoellig},
-      booktitle={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
-      year={2021},
-      volume={},
-      number={},
-      pages={},
-      doi={}
-}
-```
-
-## References
-- Nathan Michael, Daniel Mellinger, Quentin Lindsey, Vijay Kumar (2010) [*The GRASP Multiple Micro UAV Testbed*](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.169.1687&rep=rep1&type=pdf)
-- Benoit Landry (2014) [*Planning and Control for Quadrotor Flight through Cluttered Environments*](http://groups.csail.mit.edu/robotics-center/public_papers/Landry15)
-- Julian Forster (2015) [*System Identification of the Crazyflie 2.0 Nano Quadrocopter*](http://mikehamer.info/assets/papers/Crazyflie%20Modelling.pdf)
-- Carlos Luis and Jeroome Le Ny (2016) [*Design of a Trajectory Tracking Controller for a Nanoquadcopter*](https://arxiv.org/pdf/1608.05786.pdf)
-- Shital Shah, Debadeepta Dey, Chris Lovett, and Ashish Kapoor (2017) [*AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles*](https://arxiv.org/pdf/1705.05065.pdf)
-- Eric Liang, Richard Liaw, Philipp Moritz, Robert Nishihara, Roy Fox, Ken Goldberg, Joseph E. Gonzalez, Michael I. Jordan, and Ion Stoica (2018) [*RLlib: Abstractions for Distributed Reinforcement Learning*](https://arxiv.org/pdf/1712.09381.pdf)
-- Antonin Raffin, Ashley Hill, Maximilian Ernestus, Adam Gleave, Anssi Kanervisto, and Noah Dormann (2019) [*Stable Baselines3*](https://github.com/DLR-RM/stable-baselines3)
-- Guanya Shi, Xichen Shi, Michael O’Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, and Soon-Jo Chung (2019)
-[*Neural Lander: Stable Drone Landing Control Using Learned Dynamics*](https://arxiv.org/pdf/1811.08027.pdf)
-- Mikayel Samvelyan, Tabish Rashid, Christian Schroeder de Witt, Gregory Farquhar, Nantas Nardelli, Tim G. J. Rudner, Chia-Man Hung, Philip H. S. Torr, Jakob Foerster, and Shimon Whiteson (2019) [*The StarCraft Multi-Agent Challenge*](https://arxiv.org/pdf/1902.04043.pdf)
-- C. Karen Liu and Dan Negrut (2020) [*The Role of Physics-Based Simulators in Robotics*](https://www.annualreviews.org/doi/pdf/10.1146/annurev-control-072220-093055)
-- Yunlong Song, Selim Naji, Elia Kaufmann, Antonio Loquercio, and Davide Scaramuzza (2020) [*Flightmare: A Flexible Quadrotor Simulator*](https://arxiv.org/pdf/2009.00563.pdf)
+<img src="https://github.com/utiasDSL/gym-pybullet-drones/blob/master/files/readme_images/helix.gif?raw=true" alt="formation flight" width="350"> <img src="https://github.com/utiasDSL/gym-pybullet-drones/blob/master/files/readme_images/helix.png?raw=true" alt="control info" width="450">
 
+Find the project's published results at [Learning to Fly—a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control](https://ieeexplore.ieee.org/abstract/document/9635857).
 
 -----
 > University of Toronto's [Dynamic Systems Lab](https://github.com/utiasDSL) / [Vector Institute](https://github.com/VectorInstitute) / University of Cambridge's [Prorok Lab](https://github.com/proroklab) / [Mitacs](https://www.mitacs.ca/en/projects/multi-agent-reinforcement-learning-decentralized-uavugv-cooperative-exploration)
diff --git a/pyproject.toml b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "gym-pybullet-drones"
-version = "0.0.2"
+version = "0.0.3"
 description = "PyBullet Gym environments for single and multi-agent reinforcement learning of quadcopter control"
 authors = ["Jacopo Panerati <[email protected]>"]
 license = "MIT"