Merge pull request #22 from ai-winter/v1.1

V1.1

Author: omigeft

.gitignore

@@ -2,6 +2,8 @@
 __pycache__/
 build/
 devel/
+docs/
+tmp/
 python_motion_planning.egg-info/
 # local env files
 .env.local
@@ -25,6 +27,7 @@ examples/models/*
 # Editor directories and files
 .idea
 .vscode
+.pypirc
 *.suo
 *.ntvs*
 *.njsproj
@@ -34,4 +37,6 @@ examples/models/*
 *.log
 
 # auto generated files
-site/
+site/ 
+dist/
+logs/

README.md

@@ -38,15 +38,25 @@ python_motion_planning
         ├─planner
         └─plot
 ```
+
 * The global planning algorithm implementation is in the folder `global_planner` with `graph_search`, `sample_search` and `evolutionary search`.
+
 * The local planning algorithm implementation is in the folder `local_planner`.
+
 * The curve generation algorithm implementation is in the folder `curve_generation`.
 
-## Dependencies
-The code was tested in python=3.10. To install other dependencies, please run the following command in shell.
+## Install
+*(Optional)* The code was tested in python=3.10. We recommend using `conda` to install the dependencies.
+
+```shell
+conda create -n pmp python=3.10
+conda activate pmp
+```
+
+To install the repository, please run the following command in shell.
 
 ```shell
-pip install -r requirements.txt
+pip install python-motion-planning
 ```
 
 ## Run
@@ -75,11 +85,13 @@ planner = search_factory("a_star", start=(5, 5), goal=(45, 25), env=pmp.Grid(51,
 planner.run()       # run both planning and animation
 ```
 
-More examples can be found in the folder `examples`. You can also refer to the examples in the documentations generated using the following method.
+More examples can be found in the folder `examples` in the repository.
 
 ## Documentation
 
-This repository also support auto-generated documentation using mkdocs. Enter the root directory and run
+For more details, you can refer to [online documentation](https://ai-winter.github.io/python_motion_planning/).
+
+The documentation is auto-generated using mkdocs. To do this, enter the root directory and run
 
 ```shell
 python generate_mkdocs.py
@@ -115,6 +127,7 @@ Planner      | Version
 
 
 ## Local Planner
+
 | Planner     | Version                                                                                                                                                | Animation                                     
 |-------------|--------------------------------------------------------------------------------------------------------------------------------------------------------| -------------------------------------------------- 
 | **PID**     | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/python_motion_planning/blob/master/local_planner/pid.py)  | ![pid_python.svg](assets/pid_python.svg) 
@@ -126,7 +139,8 @@ Planner      | Version
 | **MPC**     | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/python_motion_planning/blob/master/local_planner/mpc.py)  | ![mpc_python.svg](assets/mpc_python.svg)
 | **MPPI**    | ![Status](https://img.shields.io/badge/develop-v1.0-red)                                                                                               |![Status](https://img.shields.io/badge/gif-none-yellow)
 | **Lattice** | ![Status](https://img.shields.io/badge/develop-v1.0-red)                                                                                               |![Status](https://img.shields.io/badge/gif-none-yellow)
-| **DDPG**    | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/python_motion_planning/blob/master/local_planner/ddpg.py) |![ddpg_python.svg](assets/ddpg_python.svg)
+| **DQN**    | ![Status](https://img.shields.io/badge/develop-v1.0-red)                                                                                               |![Status](https://img.shields.io/badge/gif-none-yellow)
+| **DDPG**    | ![Status](https://img.shields.io/badge/develop-v1.0-red)                                                                                               |![Status](https://img.shields.io/badge/gif-none-yellow)
 
 ## Curve Generation
 
@@ -145,6 +159,7 @@ Planner      | Version
 
 # Papers
 ## Global Planning
+
 * [A*: ](https://ieeexplore.ieee.org/document/4082128) A Formal Basis for the heuristic Determination of Minimum Cost Paths
 * [JPS:](https://ojs.aaai.org/index.php/AAAI/article/view/7994) Online Graph Pruning for Pathfinding On Grid Maps
 * [Lifelong Planning A*: ](https://www.cs.cmu.edu/~maxim/files/aij04.pdf) Lifelong Planning A*
@@ -168,7 +183,9 @@ Planner      | Version
 * [DDPG: ](https://arxiv.org/abs/1509.02971) Continuous control with deep reinforcement learning
 
 ## Curve Generation
+
 * [Dubins: ]() On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangents
 
 # Acknowledgment
+
 * Our visualization and animation framework of Python Version refers to [https://github.com/zhm-real/PathPlanning](https://github.com/zhm-real/PathPlanning). Thanks sincerely.