Posted on January 24, 2018 in analysis
Jupyter Notebook is a popular open-source tool used in data science. This blog post covers using Jupyter in combination with the Bobble-Bot simulator to perform an analysis of the robot's balance controller. In part one I explore downloading the simulator and using it to generate sample analysis data for Jupyter Notebook.
Posted on January 24, 2018 in analysis
This post will show how to use the library rosbag_pandas to load Gazebo ROS data into a Pandas DataFrame for a Jupyter Notebook based analysis. We first show how to setup the analysis environment using pip. Next, we create some simple plots from the command line before showing how to examine the data using Pandas within Jupyter Notebook. 
Posted on January 24, 2018 in analysis
In the final part of this series, I combine the lessons learned in part one and two to complete the analysis of Bobble-Bot's balance controller. The post covers a modular approach for rendering Matplotlib plots within Jupyter. In addition, I show how to implement a differential drive robot model using NumPy in order to post process Bobble-Bot simulation data. Finally, I conclude the series by producing several plots that capture the performance of the Bobble-Bot balance controller. 