This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
- Numpy (1.18.1)
- Scipy (1.4.1)
- Matplotlib (3.1.3)
- Shapely (1.7.0)
- Cvxopt (1.2.0)
Mask of Field (Source)
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First, a large set of 'dots' are created in a grid that captures the region.
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Then, we use matplotlib.Path to create the mask of the figure. The 'dots' that remain, are the coordinates that are inside the region.
Optimal Charging Station Location (Source)
- We use a linear program that finds the optimal locations to place the charging stations such that it minimizes the mission time of the drone per Charging Station (CS) coverage region.
Voronoi Regions (Source)
- We create Voronoi regions to specify what region the drone will be covering per CS location.
Walk (Source)
- We use a linear program to minimize the edges used to traverse the CS. The area covered by the traversal are removed from the drone mission algorithm applied to each triangular region.
Triangularization (Source)
- We triangulate each Voronoi region to apply the drone mission algorithm.
Drone mission algorithm (Source)
- Here, we show the path the drone takes in a triangular region. Each color represents a new cycle after each recharge.
Run (Source)
- This is the final product when putting the submodules together.
