Update README.md (#472)

README.md

@@ -71,11 +71,13 @@ Python codes for robotics algorithm.
    * [Contribution](#contribution)
    * [Citing](#citing)
    * [Support](#support)
+   * [Sponsors](#Sponsors)
+      * [JetBrains](#JetBrains)
    * [Authors](#authors)
 
 # What is this?
 
-This is a Python code collection of robotics algorithms, especially for autonomous navigation.
+This is a Python code collection of robotics algorithms.
 
 Features:
 
@@ -92,6 +94,8 @@ See this paper for more details:
 
 # Requirements
 
+For running each sample code:
+
 - Python 3.9.x
 
 - numpy
@@ -103,8 +107,18 @@ See this paper for more details:
 - pandas
 
 - [cvxpy](https://www.cvxpy.org/index.html) 
+
+For development:
   
-- pytest (only for unit tests)
+- pytest (for unit tests)
+  
+- pytest-xdist (for parallel unit tests)
+  
+- mypy (for type check)
+  
+- Sphinx (for document generation)
+  
+- pycodestyle (for code style check)
 
 # Documentation
 
@@ -123,11 +137,15 @@ All animation gifs are stored here: [AtsushiSakai/PythonRoboticsGifs: Animation
 > git clone https://github.com/AtsushiSakai/PythonRobotics.git
 
 
-2. Install the required libraries. You can use environment.yml with conda command.
+2. Install the required libraries.
+
+using conda :
 
 > conda env create -f environment.yml
-> using pip :-
-         pip install -r requirements.txt
+ 
+using pip :
+
+> pip install -r requirements.txt
 
 
 3. Execute python script in each directory.
@@ -150,11 +168,11 @@ This is a sensor fusion localization with Particle Filter(PF).
 
 The blue line is true trajectory, the black line is dead reckoning trajectory,
 
-and the red line is estimated trajectory with PF.
+and the red line is an estimated trajectory with PF.
 
 It is assumed that the robot can measure a distance from landmarks (RFID).
 
-This measurements are used for PF localization.
+These measurements are used for PF localization.
 
 Ref:
 
@@ -222,7 +240,7 @@ Simultaneous Localization and Mapping(SLAM) examples
 
 This is a 2D ICP matching example with singular value decomposition.
 
-It can calculate a rotation matrix and a translation vector between points to points.
+It can calculate a rotation matrix, and a translation vector between points and points.
 
 ![3](https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/SLAM/iterative_closest_point/animation.gif)
 
@@ -267,7 +285,7 @@ This is a 2D navigation sample code with Dynamic Window Approach.
 
 ### Dijkstra algorithm
 
-This is a 2D grid based shortest path planning with Dijkstra's algorithm.
+This is a 2D grid based the shortest path planning with Dijkstra's algorithm.
 
 ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/Dijkstra/animation.gif)
 
@@ -275,7 +293,7 @@ In the animation, cyan points are searched nodes.
 
 ### A\* algorithm
 
-This is a 2D grid based shortest path planning with A star algorithm.
+This is a 2D grid based the shortest path planning with A star algorithm.
 
 ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/AStar/animation.gif)
 
@@ -369,7 +387,7 @@ This is a path planning simulation with LQR-RRT\*.
 
 A double integrator motion model is used for LQR local planner.
 
-![LQRRRT](https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/LQRRRTStar/animation.gif)
+![LQR_RRT](https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/LQRRRTStar/animation.gif)
 
 Ref:
 
@@ -384,7 +402,7 @@ Motion planning with quintic polynomials.
 
 ![2](https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/QuinticPolynomialsPlanner/animation.gif)
 
-It can calculate 2D path, velocity, and acceleration profile based on quintic polynomials.
+It can calculate a 2D path, velocity, and acceleration profile based on quintic polynomials.
 
 Ref:
 
@@ -420,7 +438,7 @@ This is optimal trajectory generation in a Frenet Frame.
 
 The cyan line is the target course and black crosses are obstacles.
 
-The red line is predicted path.
+The red line is the predicted path.
 
 Ref:
 
@@ -507,9 +525,9 @@ Ref:
 
 N joint arm to a point control simulation.
 
-This is a interactive simulation.
+This is an interactive simulation.
 
-You can set the goal position of the end effector with left-click on the ploting area. 
+You can set the goal position of the end effector with left-click on the plotting area. 
 
 ![3](https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/ArmNavigation/n_joint_arm_to_point_control/animation.gif)
 
@@ -544,9 +562,9 @@ Ref:
 
 ## bipedal planner with inverted pendulum
 
-This is a bipedal planner for modifying footsteps with inverted pendulum.
+This is a bipedal planner for modifying footsteps for an inverted pendulum.
 
-You can set the footsteps and the planner will modify those automatically.
+You can set the footsteps, and the planner will modify those automatically.
 
 ![3](https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/Bipedal/bipedal_planner/animation.gif)
 
@@ -566,8 +584,6 @@ This is a list of other user's comment and references:[users\_comments](https://
 
 Any contribution is welcome!!
 
-If your PR is merged multiple times, I will add your account to the author list.
-
 # Citing
 
 If you use this project's code for your academic work, we encourage you to cite [our papers](https://arxiv.org/abs/1808.10703) 
@@ -584,26 +600,15 @@ If you or your company would like to support this project, please consider:
 
 - [One-time donation via PayPal](https://www.paypal.me/myenigmapay/)
 
+If you would like to support us in some other way, please contact with creating an issue.
+
+# Sponsors
+
+## [JetBrains](https://www.jetbrains.com/)
+
+They are providing a free license of their IDEs for this OSS development.   
+
 # Authors
 
-- [Atsushi Sakai](https://github.com/AtsushiSakai/)
-
-- [Daniel Ingram](https://github.com/daniel-s-ingram)
-
-- [Joe Dinius](https://github.com/jwdinius)
-
-- [Karan Chawla](https://github.com/karanchawla)
-
-- [Antonin RAFFIN](https://github.com/araffin)
-
-- [Alexis Paques](https://github.com/AlexisTM)
-
-- [Ryohei Sasaki](https://github.com/rsasaki0109)
-
-- [Göktuğ Karakaşlı](https://github.com/goktug97)
-
-- [Guillaume Jacquenot](https://github.com/Gjacquenot)
-
-- [Erwin Lejeune](https://github.com/guilyx)
-
+- [Contributors to AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/graphs/contributors)
 

environment.yml

@@ -7,4 +7,3 @@ dependencies:
 - pandas
 - cvxpy
 - matplotlib
-- coverage

requirements.txt

@@ -3,4 +3,3 @@ scipy == 1.6.0
 pandas == 1.2.1
 matplotlib == 3.3.3
 cvxpy == 1.1.7
-pytest == 6.2.2