A dataset consisting of 46K MCPP problems with solutions found by DARP.
DARP is an efficient algorithm for multi-agent coverage path planning (MCPP). This dataset contains 46537 examples of MCPP problems on a 10x10 map with solutions found by DARP after a maximum of 100 iterations. Each problem involves four agents and 10 randomly positioned obstacles. The solutions are given as bitmaps denoting the allocated areas for each agent.
$ pip install git+https://github.com/oelin/darp-46k
The dataset is encoded in a compressed, non-standard format optimized for the particular information required about each example. Nonetheless, it can be easily loaded using the load_data()
method.
>>> import darp_46k
>>> data = darp_46k.load_data()
Each example in the dataset is a 3-tuple containing the following:
agent_coordinates
- a list of(y, x)
coordinates denoting the initial positions of each agent on the map.obstacle_coordinates
- a list of(y, x)
coordinates denoting the positions of each obstacle on the map.solutions
- a NumPy array of bitmaps denoting the allocated area for each agent.