added changelog

.all-contributorsrc

@@ -0,0 +1,71 @@
+{
+  "files": [
+    "README.md"
+  ],
+  "imageSize": 100,
+  "commit": false,
+  "contributors": [
+    {
+      "login": "ManosMagnus",
+      "name": "Manos Kirtas",
+      "avatar_url": "https://avatars.githubusercontent.com/u/10010230?v=4",
+      "profile": "http://eakirtas.webpages.auth.gr/",
+      "contributions": [
+        "code"
+      ]
+    },
+    {
+      "login": "tsampazk",
+      "name": "Kostas Tsampazis",
+      "avatar_url": "https://avatars.githubusercontent.com/u/27914645?v=4",
+      "profile": "https://github.com/tsampazk",
+      "contributions": [
+        "code"
+      ]
+    },
+    {
+      "login": "KelvinYang0320",
+      "name": "Jiun Kai Yang",
+      "avatar_url": "https://avatars.githubusercontent.com/u/49781698?v=4",
+      "profile": "https://www.linkedin.com/in/kelvin-yang-b7b508198/",
+      "contributions": [
+        "code"
+      ]
+    },
+    {
+      "login": "MentalGear",
+      "name": "MentalGear",
+      "avatar_url": "https://avatars.githubusercontent.com/u/2837147?v=4",
+      "profile": "https://github.com/MentalGear",
+      "contributions": [
+        "ideas"
+      ]
+    },
+    {
+      "login": "DreamtaleCore",
+      "name": "Dreamtale",
+      "avatar_url": "https://avatars.githubusercontent.com/u/12713528?v=4",
+      "profile": "https://github.com/DreamtaleCore",
+      "contributions": [
+        "bug"
+      ]
+    },
+    {
+      "login": "NickKok",
+      "name": "Nikolaos Kokkinis-Ntrenis",
+      "avatar_url": "https://avatars.githubusercontent.com/u/8222731?v=4",
+      "profile": "https://nickkok.github.io/my-website/",
+      "contributions": [
+        "code",
+        "doc",
+        "ideas"
+      ]
+    }
+  ],
+  "contributorsPerLine": 7,
+  "projectName": "deepbots",
+  "projectOwner": "aidudezzz",
+  "repoType": "github",
+  "repoHost": "https://github.com",
+  "skipCi": true
+}

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.1.3-dev1
+current_version = 0.1.3-dev4
 commit = True
 tag = True
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<build>\d+))?
@@ -20,3 +20,7 @@ values =
 [bumpversion:file:VERSION]
 
 [bumpversion:file:setup.py]
+
+[bumpversion:file:deepbots/__init__.py]
+search = "{current_version}"
+replace = "{new_version}"

.github/workflows/changelog_update.yaml

@@ -0,0 +1,30 @@
+name: Generate Changelog
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  generate_changelog:
+    name: Update Changelog
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout dev
+        uses: actions/checkout@v2
+
+      - name: Generate changelog
+        uses: charmixer/[email protected]
+        with:
+          token: ${{ secrets.AIDUDEZZ_BOT_TOKEN }}
+
+      - name: Commit files
+        run: |
+          git config --local user.email ${{ secrets.AIDUDEZZZ_BOT_EMAIL }}
+          git config --local user.name ${{ secrets.AIDUDEZZZ_BOT_USER }}
+          git add CHANGELOG.md && git commit -m 'Updated CHANGELOG.md' && echo "push=true" >> $GITHUB_ENV || echo "No changes to CHANGELOG.md"
+      - name: Push changes
+        if: env.push == 'true'
+        uses: ad-m/github-push-action@master
+        with:
+          github_token: ${{ secrets.AIDUDEZZ_BOT_TOKEN }}
+          branch: main

.github/workflows/python_build.yaml

@@ -7,7 +7,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.5, 3.6, 3.7]
+        python-version: [3.7, 3.8, 3.9]
 
     steps:
       - uses: actions/checkout@v1

.isort.cfg

@@ -1,2 +1,2 @@
 [settings]
-known_third_party = controller,numpy,setuptools,tensorboardX
+known_third_party = controller,cv2,gym,numpy,ray,setuptools,tensorboardX

.pre-commit-config.yaml

@@ -34,6 +34,7 @@ repos:
     hooks:
       - id: prettier
         args: [--prose-wrap=always, --print-width=79]
+        exclude: README.md
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v2.4.0

README.md

@@ -1,4 +1,12 @@
-# deepbots
+<p align="left">
+    <img src="https://raw.githubusercontent.com/aidudezzz/deepbots-swag/main/logo/deepbots_full.png">
+</p>
+
+[![Version](https://img.shields.io/pypi/v/deepbots?color=green)](https://pypi.org/project/deepbots/)
+[![Dev Version](https://img.shields.io/github/v/tag/aidudezzz/deepbots?include_prereleases&label=test-pypi&color=green)](https://test.pypi.org/project/deepbots/)
+[![Downloads](https://static.pepy.tech/personalized-badge/deepbots?period=total&units=international_system&left_color=grey&right_color=green&left_text=Downloads)](https://pepy.tech/project/deepbots)
+[![License](https://img.shields.io/github/license/aidudezzz/deepbots?color=green)](https://github.com/aidudezzz/deepbots/blob/dev/LICENSE)
+[![All Contributors](https://img.shields.io/badge/all_contributors-6-orange.svg?style=flat-square)](#contributors-)
 
 Deepbots is a simple framework which is used as "middleware" between the free
 and open-source [Cyberbotics' Webots](https://cyberbotics.com/) robot simulator
@@ -60,16 +68,12 @@ https://link.springer.com/chapter/10.1007/978-3-030-49186-4_6
     and Tsampazis, K.
     and Passalis, N.
     and Tefas, A.",
-    editor="Maglogiannis, Ilias
-    and Iliadis, Lazaros
-    and Pimenidis, Elias",
     title="Deepbots: A Webots-Based Deep Reinforcement Learning Framework for Robotics",
     booktitle="Artificial Intelligence Applications and Innovations",
     year="2020",
     publisher="Springer International Publishing",
     address="Cham",
     pages="64--75",
-    abstract="Deep Reinforcement Learning (DRL) is increasingly used to train robots to perform complex and delicate tasks, while the development of realistic simulators contributes to the acceleration of research on DRL for robotics. However, it is still not straightforward to employ such simulators in the typical DRL pipeline, since their steep learning curve and the enormous amount of development required to interface with DRL methods significantly restrict their use by researchers. To overcome these limitations, in this work we present an open-source framework that combines an established interface used by DRL researchers, the OpenAI Gym interface, with the state-of-the-art Webots robot simulator in order to provide a standardized way to employ DRL in various robotics scenarios. Deepbots aims to enable researchers to easily develop DRL methods in Webots by handling all the low-level details and reducing the required development effort. The effectiveness of the proposed framework is demonstrated through code examples, as well as using three use cases of varying difficulty.",
     isbn="978-3-030-49186-4"
 }
 
@@ -142,26 +146,27 @@ those who are familiar with the OpenAI gym environment. More specifically,
 algorithms and follows the OpenAI Gym environment logic. The Deepbots framework
 provides different levels of abstraction according to the user's needs.
 Moreover, a goal of the framework is to provide different wrappers for a wide
-range of robots. 
+range of robots.
 
 Deepbots also provides a default implementation of the `reset()` method,
-leveraging Webots' built-in simulation reset functions, removing the need
-for the user to implement reset procedures for simpler use-cases. It is 
-always possible to override this method and implement any custom reset
-procedure, as needed.
+leveraging Webots' built-in simulation reset functions, removing the need for
+the user to implement reset procedures for simpler use-cases. It is always
+possible to override this method and implement any custom reset procedure, as
+needed.
 
 #### Emitter - receiver scheme
 
-Currently, the communication between the `Supervisor` and the
-`Robot` is achieved via an `emitter` and a `receiver`. Separating the `Supervisor`
-from the `Robot`, deepbots can fit a variety of use-cases, e.g. multiple
-`Robots` collecting experience and a `Supervisor` controlling them with a single
-agent. The way Webots implements `emitter`/`receiver` communication requires messages 
-to be packed and unpacked, which introduces an overhead that becomes prohibiting in 
-use-cases where the observations are high-dimensional or long, such as camera images. 
-Deepbots provides another partially abstract class that combines the `Supervisor` 
-and the `Robot` into one controller and circumvents that issue, while being less
-flexible, which is discussed [later](#combined-robot-supervisor-scheme).
+Currently, the communication between the `Supervisor` and the `Robot` is
+achieved via an `emitter` and a `receiver`. Separating the `Supervisor` from
+the `Robot`, deepbots can fit a variety of use-cases, e.g. multiple `Robots`
+collecting experience and a `Supervisor` controlling them with a single agent.
+The way Webots implements `emitter`/`receiver` communication requires messages
+to be packed and unpacked, which introduces an overhead that becomes
+prohibiting in use-cases where the observations are high-dimensional or long,
+such as camera images. Deepbots provides another partially abstract class that
+combines the `Supervisor` and the `Robot` into one controller and circumvents
+that issue, while being less flexible, which is discussed
+[later](#combined-robot-supervisor-scheme).
 
 <p align="center">
     <img src="https://raw.githubusercontent.com/aidudezzz/deepbots/dev/doc/img/deepbots_overview.png">
@@ -170,31 +175,40 @@ flexible, which is discussed [later](#combined-robot-supervisor-scheme).
 On one hand, the `emitter` is an entity which is provided by Webots, that
 broadcasts messages to the world. On the other hand, the `receiver` is an
 entity that is used to receive messages from the `World`. Consequently, the
-agent-environment loop is transformed accordingly. Firstly, the `Robot` uses its
-sensors to retrieve the observation from the `World` and in turn uses the `emitter`
-component to broadcast this observation. Secondly, the `Supervisor` receives the
-observation via the `receiver` component and in turn, the agent uses it to choose
-an action. It should be noted that the observation the agent uses might be
-extended from the `Supervisor`. For example, a model might use LiDAR sensors
-installed on the `Robot`, but also the Euclidean distance between the `Robot` and
-an object. As it is expected, the `Robot` does not know the Euclidean distance,
-only the `Supervisor` can calculate it, because it has access to all entities in
-the `World`.
+agent-environment loop is transformed accordingly. Firstly, the `Robot` uses
+its sensors to retrieve the observation from the `World` and in turn uses the
+`emitter` component to broadcast this observation. Secondly, the `Supervisor`
+receives the observation via the `receiver` component and in turn, the agent
+uses it to choose an action. It should be noted that the observation the agent
+uses might be extended from the `Supervisor`. For example, a model might use
+LiDAR sensors installed on the `Robot`, but also the Euclidean distance between
+the `Robot` and an object. As it is expected, the `Robot` does not know the
+Euclidean distance, only the `Supervisor` can calculate it, because it has
+access to all entities in the `World`.
+
+You can follow the 
+[emitter-receiver scheme tutorial](https://github.com/aidudezzz/deepbots-tutorials/blob/master/emitterReceiverSchemeTutorial/README.md)
+to get started and work your way up from there.
 
 <p align="center">
     <img src="https://raw.githubusercontent.com/aidudezzz/deepbots/dev/doc/img/workflow_diagram.png">
 </p>
 
 #### Combined Robot-Supervisor scheme
 
-As mentioned earlier, in use-cases where the observation transmitted between 
-the `Robot` and the `Supervisor` is high-dimensional or long, e.g. high resolution 
-images taken from a camera, a significant overhead is introduced. This is circumvented 
-by inheriting and implementing the partially abstract `RobotSupervisor` that combines 
-the `Robot controller` and the `Supervisor Controller` into one, forgoing all 
-`emitter`/`receiver` communication. This new controller runs on the `Robot`, but 
-requires `Supervisor` privileges and is limited to one `Robot`, one `Supervisor`.  
+As mentioned earlier, in use-cases where the observation transmitted between
+the `Robot` and the `Supervisor` is high-dimensional or long, e.g. high
+resolution images taken from a camera, a significant overhead is introduced.
+This is circumvented by inheriting and implementing the partially abstract
+`RobotSupervisor` that combines the `Robot controller` and the
+`Supervisor Controller` into one, forgoing all `emitter`/`receiver`
+communication. This new controller runs on the `Robot`, but requires
+`Supervisor` privileges and is limited to one `Robot`, one `Supervisor`.
 
+You can follow the 
+[robot-supervisor scheme tutorial](https://github.com/aidudezzz/deepbots-tutorials/tree/master/robotSupervisorSchemeTutorial)
+to get started and work your way up from there. We recommended this
+tutorial to get started with deepbots.
 
 ### Abstraction Levels
 
@@ -203,15 +217,49 @@ aim of the framework is to enable people to use Reinforcement Learning in
 Webots. More specifically, we can consider deepbots as a wrapper of Webots
 exposing an OpenAI gym style interface. For this reason there are multiple
 levels of abstraction. For example, a user can choose if they want to use CSV
-`emitter`/`receiver` or if they want to make an implementation from scratch. 
-In the top level of the abstraction hierarchy is the `SupervisorEnv` which is the
+`emitter`/`receiver` or if they want to make an implementation from scratch. In
+the top level of the abstraction hierarchy is the `SupervisorEnv` which is the
 OpenAI gym interface. Below that level there are partially implemented classes
-with common functionality. These implementations aim to hide the communication 
+with common functionality. These implementations aim to hide the communication
 between the `Supervisor` and the `Robot`, as described in the two different
-schemes ealier. Similarly, in the `emitter`/`receiver` scheme the `Robot` 
-also has different abstraction levels. According to their needs, users can choose 
-either to process the messages received from the `Supervisor` themselves or 
-use the existing implementations.
-
-### Acknowledgments  
-This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871449 (OpenDR). This publication reflects the authors’ views only. The European Commission is not responsible for any use that may be made of the information it contains.
+schemes ealier. Similarly, in the `emitter`/`receiver` scheme the `Robot` also
+has different abstraction levels. According to their needs, users can choose
+either to process the messages received from the `Supervisor` themselves or use
+the existing implementations.
+
+### Acknowledgments
+
+This project has received funding from the European Union's Horizon 2020
+research and innovation programme under grant agreement No 871449 (OpenDR).
+This publication reflects the authors’ views only. The European Commission is
+not responsible for any use that may be made of the information it contains.
+
+## Contributors ✨
+
+Thanks goes to these wonderful people
+([emoji key](https://allcontributors.org/docs/en/emoji-key)):
+
+<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
+<!-- prettier-ignore-start -->
+<!-- markdownlint-disable -->
+<table>
+  <tr>
+    <td align="center"><a href="http://eakirtas.webpages.auth.gr/"><img src="https://avatars.githubusercontent.com/u/10010230?v=4?s=100" width="100px;" alt=""/><br /><sub><b>Manos Kirtas</b></sub></a><br /><a href="https://github.com/aidudezzz/deepbots/commits?author=ManosMagnus" title="Code">💻</a></td>
+    <td align="center"><a href="https://github.com/tsampazk"><img src="https://avatars.githubusercontent.com/u/27914645?v=4?s=100" width="100px;" alt=""/><br /><sub><b>Kostas Tsampazis</b></sub></a><br /><a href="https://github.com/aidudezzz/deepbots/commits?author=tsampazk" title="Code">💻</a></td>
+    <td align="center"><a href="https://www.linkedin.com/in/kelvin-yang-b7b508198/"><img src="https://avatars.githubusercontent.com/u/49781698?v=4?s=100" width="100px;" alt=""/><br /><sub><b>Jiun Kai Yang</b></sub></a><br /><a href="https://github.com/aidudezzz/deepbots/commits?author=KelvinYang0320" title="Code">💻</a></td>
+    <td align="center"><a href="https://github.com/MentalGear"><img src="https://avatars.githubusercontent.com/u/2837147?v=4?s=100" width="100px;" alt=""/><br /><sub><b>MentalGear</b></sub></a><br /><a href="#ideas-MentalGear" title="Ideas, Planning, & Feedback">🤔</a></td>
+    <td align="center"><a href="https://github.com/DreamtaleCore"><img src="https://avatars.githubusercontent.com/u/12713528?v=4?s=100" width="100px;" alt=""/><br /><sub><b>Dreamtale</b></sub></a><br /><a href="https://github.com/aidudezzz/deepbots/issues?q=author%3ADreamtaleCore" title="Bug reports">🐛</a></td>
+    <td align="center"><a href="https://nickkok.github.io/my-website/"><img src="https://avatars.githubusercontent.com/u/8222731?v=4?s=100" width="100px;" alt=""/><br /><sub><b>Nikolaos Kokkinis-Ntrenis</b></sub></a><br /><a href="https://github.com/aidudezzz/deepbots/commits?author=NickKok" title="Code">💻</a> <a href="https://github.com/aidudezzz/deepbots/commits?author=NickKok" title="Documentation">📖</a> <a href="#ideas-NickKok" title="Ideas, Planning, & Feedback">🤔</a></td>
+  </tr>
+</table>
+
+<!-- markdownlint-restore -->
+<!-- prettier-ignore-end -->
+
+<!-- ALL-CONTRIBUTORS-LIST:END -->
+
+This project follows the
+[all-contributors](https://github.com/all-contributors/all-contributors)
+specification. Contributions of any kind welcome!
+
+<b> Special thanks to <a href='https://www.papanikolaouev.com/'>Papanikolaou Evangelia</a> </b> for designing project's logo! </b> 

VERSION

@@ -1 +1 @@
-0.1.3-dev1
+0.1.3-dev4

deepbots/__init__.py

@@ -1 +1 @@
-__version__ = "0.0.0.11-pre"
+__version__ = "0.1.3-dev4"

deepbots/robots/__init__.py

@@ -0,0 +1,2 @@
+from deepbots.robots.controllers.csv_robot import CSVRobot
+from deepbots.robots.controllers.emitter_receiver_robot import EmitterReceiverRobot