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July 13, 2016

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Gradient Descent approach for PID parameter tuning What is gradient descent ? Why it is with PID controller? Why only gradient descent ? What is the befit we will get with this ? All these questions will be answered in this post. Using Gradient descent we have tested a way point navigation task with Parrot Ardrone 2.0 with PTAM. We have used this Gradient Descent method to tune the PID parameters of a controller designed for UAV Quadrotor. This work has been published in IEEE Xplore as a proceeding of ICAR 2017 . Publication URL : http://ieeexplore.ieee.org/abstract/document/8023513/

Aruco M arker Tracking with ARDrone2.0 Parrot ARDrone 2.0 is a well know drone to all and its mostly used for research. Here I did few formations using Aruco markers . This Project includes Aruco Marker Following Ardrone Gradient Descent Based PID Controller First lets make the drone follows you, for this you need Aruco marker ( here ) ( documentation ) Parrot Ardrone ROS Indigo or above ( here ) Download ardrone_autonomy package ( here ) Aruco library is an extra module in Open CV 3.0, if you are using other versions of openCV, try installing open CV 3.0 extra modules with your current openCV version. (May be you need to dig up into this) Note : I recommend Ubuntu 16.04 with ROS Kinetic can make life easier for this project Install ardrone_autonomy package from here . Then download our repository ( here ) to your ros workspace. Creating of ros workspace ( here ) is already done in the page of downloading ardrone_autonomy package. Before star...

Autonomous Landing of UAV Quadrotor using Reinforcement learning

In this post we will make the drone to learn how to fly. The drone learned how to fly in a square of different heights. The controller learned by the drone has been tested for the landing task on a marker. Learning : Landing on Marker In gazebo: Real time Test:

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