[ros-users] [Discourse.ros.org] [ROS Projects] Precision Agriculture Simulation with a Quadcopter in Gazebo

[Tahsin Kose]

You can see the version 3 of exploration [in this video](https://www.youtube.com/watch?v=-Hrpk1CQATs).

The problem diagnosed as _"Return to Home Problem"_ is mitigated with the addition of randomization into the system. So that, it both curates the distant and closest frontiers of any degree. With a fully randomized decision making process, it naturally boosted up the performance and with this sole trick, the exploration rate has reached to 27-28%. Then, another problem is diagnosed. The frontiers were so granular that almost identical frontiers are behaved as different and drone visited same places repetitively. In order to resolve this issue a grid approach is embraced in which a cell could be visited only once. This approach increased the exploration rate a lot. For example in 25x25 case the exploration rate reached up to 32%. Actually, as long as the grid size is reduced, the exploration rate increases. However, of course there is a saddle point which results in the complete failure of the system regarding to new frontier discovery if overcrossed. Consider 1x1 case to unde
 rstand that.

In total; 15x15, 14x14 and 13x13 cases are experimented. Their respective exploration rates were 35.6%, 37.4% and 40.7%. During experimentations, I have diagnosed another interesting feature of the problem. OctoMap is not uniformly investigated in terms of frontiers, therefore a side of the volume remains highly explored whereas the other does remain unexplored. In order to mitigate this problem, and have higher exploration rates in 10 minutes one can embrace a better, more advanced heuristics.





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