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updated README.md

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mcarfagno 2020-04-07 17:09:13 +01:00
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@ -6,22 +6,22 @@ Python implementation of mpc controller for path tracking.
The MPC is a model predictive path following controller which does follow a predefined reference path Xref and Yref by solving an optimization problem. The resulting optimization problem is shown in the following equation:
![](img/quicklatex1.gif)
![](img/quicklatex1.png)
The vehicle dynamics are described by the differential drive model:
![](img/quicklatex2.gif)
![](img/quicklatex2.png)
The state variables of the model are:
* $x$ coordinate of the robot
* $y$ coordinate of the robot
* $\theta$ heading of the robot
* **x** coordinate of the robot
* **y** coordinate of the robot
* **theta** heading of the robot
The inputs of the model are:
* $v$ linear velocity of the robot
* $w$ angular velocity of the robot
* **v** linear velocity of the robot
* **w** angular velocity of the robot
## Demo

14
README.md
View File

@ -6,22 +6,22 @@ Python implementation of mpc controller for path tracking.
The MPC is a model predictive path following controller which does follow a predefined reference path Xref and Yref by solving an optimization problem. The resulting optimization problem is shown in the following equation:
![](img/quicklatex1.gif)
![](img/quicklatex1.png)
The vehicle dynamics are described by the differential drive model:
![](img/quicklatex2.gif)
![](img/quicklatex2.png)
The state variables of the model are:
* $x$ coordinate of the robot
* $y$ coordinate of the robot
* $\theta$ heading of the robot
* **x** coordinate of the robot
* **y** coordinate of the robot
* **theta** heading of the robot
The inputs of the model are:
* $v$ linear velocity of the robot
* $w$ angular velocity of the robot
* **v** linear velocity of the robot
* **w** angular velocity of the robot
## Demo