Data set: Industrial IoT-driven remote path planning

<p>This compressed file contains data from three different experiments during the&nbsp; IIoT-REPLAN experimentation phase&nbsp;(Industrial IoT-drive remote path planning). IIoT-REPLAN was&nbsp;funded by an open call from the&nbsp;&nbsp;H2020 Fed4FIRE+ project.</p> <p>Contents:</p> <p>A. astar.csv<br> This file contains the timestamp of each movement of the Robot and the uncertainty (d) at each specific time that Switch 1 was checked. The first two columns refer to seconds while the third one is a scalar value. The total duration of the experiment is 62.33 sec and the setup of this experiment is the real time application of the Astar Algorithm with the localization being based only on the sensor of the Robot</p> <p><br> B. Dijkstra.csv&nbsp;<br> In this experiment the full functionality of the switching system proposed in this work is highlighted.&nbsp;</p> <p>C. Cloud.csv<br> In this experiment the localization algorithm and the path planning algorithm are always executed on the cloud.</p> <p>In both B,C experiments the values of each column are explained inside the Dijkstra.csv&nbsp;</p> <p>Also, two pictures of singlie vision-based self localization are included.&nbsp;</p> <p>A more detailed exposition on all of the above can be found at&nbsp;<br> github link : https://github.com/maravger/alphabot-ppl</p>